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We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.

The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.

When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.

To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

Exponential Random Numbers

NPM versionBuild StatusCoverage Status

Create an array containing pseudorandom numbers drawn from an exponential distribution.

Installation

npm install @stdlib/random-array-exponential

Alternatively,

  • To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
  • If you are using Deno, visit the deno branch (see README for usage intructions).
  • For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).

The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.

To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.

Usage

varexponential=require('@stdlib/random-array-exponential');

exponential( len, lambda[, options] )

Returns an array containing pseudorandom numbers drawn from an exponential distribution.

varout=exponential(10,2.0);// returns <Float64Array>

The function has the following parameters:

  • len: output array length.
  • lambda: rate parameter.
  • options: function options.

The function accepts the following options:

By default, the function returns a Float64Array. To return an array having a different data type, set the dtype option.

varopts={'dtype': 'generic'};varout=exponential(10,2.0,opts);// returns [...]

exponential.assign( lambda, out )

Fills an array with pseudorandom numbers drawn from an exponential distribution.

varzeros=require('@stdlib/array-zeros');varx=zeros(10,'float64');// returns <Float64Array>varout=exponential.assign(2.0,x);// returns <Float64Array>varbool=(out===x);// returns true

The function has the following parameters:

  • lambda: rate parameter.
  • out: output array.

exponential.factory( [lambda, ][options] )

Returns a function for creating arrays containing pseudorandom numbers drawn from an exponential distribution.

varrandom=exponential.factory();varout=random(10,2.0);// returns <Float64Array>varlen=out.length;// returns 10

If provided lambda, the returned generator returns random variates from the specified distribution.

varrandom=exponential.factory(2.0);varout=random(10);// returns <Float64Array>out=random(10);// returns <Float64Array>

If not provided lambda, the returned generator requires that lambda be provided at each invocation.

varrandom=exponential.factory();varout=random(10,2.0);// returns <Float64Array>out=random(10,2.0);// returns <Float64Array>

The function accepts the following options:

  • prng: pseudorandom number generator for generating uniformly distributed pseudorandom numbers on the interval [0,1). If provided, the function ignores both the state and seed options. In order to seed the underlying pseudorandom number generator, one must seed the provided prng (assuming the provided prng is seedable).
  • seed: pseudorandom number generator seed.
  • state: a Uint32Array containing pseudorandom number generator state. If provided, the function ignores the seed option.
  • copy: boolean indicating whether to copy a provided pseudorandom number generator state. Setting this option to false allows sharing state between two or more pseudorandom number generators. Setting this option to true ensures that an underlying generator has exclusive control over its internal state. Default: true.
  • dtype: default output array data type. Must be a real-valued floating-point data type or "generic". Default: 'float64'.

To use a custom PRNG as the underlying source of uniformly distributed pseudorandom numbers, set the prng option.

varminstd=require('@stdlib/random-base-minstd');varopts={'prng': minstd.normalized};varrandom=exponential.factory(2.0,opts);varout=random(10);// returns <Float64Array>

To seed the underlying pseudorandom number generator, set the seed option.

varopts={'seed': 12345};varrandom=exponential.factory(2.0,opts);varout=random(10,opts);// returns <Float64Array>

The returned function accepts the following options:

To override the default output array data type, set the dtype option.

varrandom=exponential.factory(2.0);varout=random(10);// returns <Float64Array>varopts={'dtype': 'generic'};out=random(10,opts);// returns [...]

exponential.PRNG

The underlying pseudorandom number generator.

varprng=exponential.PRNG;// returns <Function>

exponential.seed

The value used to seed the underlying pseudorandom number generator.

varseed=exponential.seed;// returns <Uint32Array>

If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.

varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varseed=random.seed;// returns null

exponential.seedLength

Length of underlying pseudorandom number generator seed.

varlen=exponential.seedLength;// returns <number>

If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.

varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varlen=random.seedLength;// returns null

exponential.state

Writable property for getting and setting the underlying pseudorandom number generator state.

varstate=exponential.state;// returns <Uint32Array>

If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.

varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varstate=random.state;// returns null

exponential.stateLength

Length of underlying pseudorandom number generator state.

varlen=exponential.stateLength;// returns <number>

If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.

varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varlen=random.stateLength;// returns null

exponential.byteLength

Size (in bytes) of underlying pseudorandom number generator state.

varsz=exponential.byteLength;// returns <number>

If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.

varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varsz=random.byteLength;// returns null

Notes

  • If PRNG state is "shared" (meaning a state array was provided during function creation and not copied) and one sets the underlying generator state to a state array having a different length, the function returned by the factory method does not update the existing shared state and, instead, points to the newly provided state array. In order to synchronize the output of the underlying generator according to the new shared state array, the state array for each relevant creation function and/or PRNG must be explicitly set.
  • If PRNG state is "shared" and one sets the underlying generator state to a state array of the same length, the PRNG state is updated (along with the state of all other creation functions and/or PRNGs sharing the PRNG's state array).

Examples

varlogEach=require('@stdlib/console-log-each');varexponential=require('@stdlib/random-array-exponential');// Create a function for generating random arrays originating from the same state:varrandom=exponential.factory(2.0,{'state': exponential.state,'copy': true});// Generate 3 arrays:varx1=random(5);varx2=random(5);varx3=random(5);// Print the contents:logEach('%f, %f, %f',x1,x2,x3);// Create another function for generating random arrays with the original state:random=exponential.factory(2.0,{'state': exponential.state,'copy': true});// Generate a single array which replicates the above pseudorandom number generation sequence:varx4=random(15);// Print the contents:logEach('%f',x4);

See Also

Notice

This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.

For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.

Community

Chat

License

See LICENSE.

Copyright

Copyright © 2016-2026. The Stdlib Authors.

About

Create an array containing pseudorandom numbers drawn from an exponential distribution.

github.com/stdlib-js/stdlib

Topics

continuousexpexponentialgeneratorjavascriptmathmathematicsnodenode-jsnodejsprngpseudorandomrandrandomrngseedseedablestatisticsstatsstdlib

Resources

Readme
Apache-2.0 license

Code of conduct

Code of conduct

Contributing

Contributing

Security policy

Security policy
Activity
Custom properties

Stars

1 star

Watchers

2 watching

Forks

0 forks
Report repository

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GitHub - stdlib-js/random-array-exponential: Create an array containing pseudorandom numbers drawn from an exponential distribution. · GitHub
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About stdlib...

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.
The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.
When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.
To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!
Exponential Random Numbers
NPM versionBuild StatusCoverage Status
Create an array containing pseudorandom numbers drawn from an exponential distribution.
Installation
npm install @stdlib/random-array-exponential
Alternatively,
  • To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
  • If you are using Deno, visit the deno branch (see README for usage intructions).
  • For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).
The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.
To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.
Usage
varexponential=require('@stdlib/random-array-exponential');
exponential( len, lambda[, options] )
Returns an array containing pseudorandom numbers drawn from an exponential distribution.
varout=exponential(10,2.0);// returns <Float64Array>
The function has the following parameters:
  • len: output array length.
  • lambda: rate parameter.
  • options: function options.
The function accepts the following options:
By default, the function returns a Float64Array. To return an array having a different data type, set the dtype option.
varopts={'dtype': 'generic'};varout=exponential(10,2.0,opts);// returns [...]
exponential.assign( lambda, out )
Fills an array with pseudorandom numbers drawn from an exponential distribution.
varzeros=require('@stdlib/array-zeros');varx=zeros(10,'float64');// returns <Float64Array>varout=exponential.assign(2.0,x);// returns <Float64Array>varbool=(out===x);// returns true
The function has the following parameters:
  • lambda: rate parameter.
  • out: output array.
exponential.factory( [lambda, ][options] )
Returns a function for creating arrays containing pseudorandom numbers drawn from an exponential distribution.
varrandom=exponential.factory();varout=random(10,2.0);// returns <Float64Array>varlen=out.length;// returns 10
If provided lambda, the returned generator returns random variates from the specified distribution.
varrandom=exponential.factory(2.0);varout=random(10);// returns <Float64Array>out=random(10);// returns <Float64Array>
If not provided lambda, the returned generator requires that lambda be provided at each invocation.
varrandom=exponential.factory();varout=random(10,2.0);// returns <Float64Array>out=random(10,2.0);// returns <Float64Array>
The function accepts the following options:
  • prng: pseudorandom number generator for generating uniformly distributed pseudorandom numbers on the interval [0,1). If provided, the function ignores both the state and seed options. In order to seed the underlying pseudorandom number generator, one must seed the provided prng (assuming the provided prng is seedable).
  • seed: pseudorandom number generator seed.
  • state: a Uint32Array containing pseudorandom number generator state. If provided, the function ignores the seed option.
  • copy: boolean indicating whether to copy a provided pseudorandom number generator state. Setting this option to false allows sharing state between two or more pseudorandom number generators. Setting this option to true ensures that an underlying generator has exclusive control over its internal state. Default: true.
  • dtype: default output array data type. Must be a real-valued floating-point data type or "generic". Default: 'float64'.
To use a custom PRNG as the underlying source of uniformly distributed pseudorandom numbers, set the prng option.
varminstd=require('@stdlib/random-base-minstd');varopts={'prng': minstd.normalized};varrandom=exponential.factory(2.0,opts);varout=random(10);// returns <Float64Array>
To seed the underlying pseudorandom number generator, set the seed option.
varopts={'seed': 12345};varrandom=exponential.factory(2.0,opts);varout=random(10,opts);// returns <Float64Array>
The returned function accepts the following options:
To override the default output array data type, set the dtype option.
varrandom=exponential.factory(2.0);varout=random(10);// returns <Float64Array>varopts={'dtype': 'generic'};out=random(10,opts);// returns [...]
exponential.PRNG
The underlying pseudorandom number generator.
varprng=exponential.PRNG;// returns <Function>
exponential.seed
The value used to seed the underlying pseudorandom number generator.
varseed=exponential.seed;// returns <Uint32Array>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varseed=random.seed;// returns null
exponential.seedLength
Length of underlying pseudorandom number generator seed.
varlen=exponential.seedLength;// returns <number>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varlen=random.seedLength;// returns null
exponential.state
Writable property for getting and setting the underlying pseudorandom number generator state.
varstate=exponential.state;// returns <Uint32Array>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varstate=random.state;// returns null
exponential.stateLength
Length of underlying pseudorandom number generator state.
varlen=exponential.stateLength;// returns <number>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varlen=random.stateLength;// returns null
exponential.byteLength
Size (in bytes) of underlying pseudorandom number generator state.
varsz=exponential.byteLength;// returns <number>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varsz=random.byteLength;// returns null
Notes
  • If PRNG state is "shared" (meaning a state array was provided during function creation and not copied) and one sets the underlying generator state to a state array having a different length, the function returned by the factory method does not update the existing shared state and, instead, points to the newly provided state array. In order to synchronize the output of the underlying generator according to the new shared state array, the state array for each relevant creation function and/or PRNG must be explicitly set.
  • If PRNG state is "shared" and one sets the underlying generator state to a state array of the same length, the PRNG state is updated (along with the state of all other creation functions and/or PRNGs sharing the PRNG's state array).
Examples
varlogEach=require('@stdlib/console-log-each');varexponential=require('@stdlib/random-array-exponential');// Create a function for generating random arrays originating from the same state:varrandom=exponential.factory(2.0,{'state': exponential.state,'copy': true});// Generate 3 arrays:varx1=random(5);varx2=random(5);varx3=random(5);// Print the contents:logEach('%f, %f, %f',x1,x2,x3);// Create another function for generating random arrays with the original state:random=exponential.factory(2.0,{'state': exponential.state,'copy': true});// Generate a single array which replicates the above pseudorandom number generation sequence:varx4=random(15);// Print the contents:logEach('%f',x4);
See Also
Notice
This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
Community
Chat
License
See LICENSE.
Copyright
Copyright © 2016-2026. The Stdlib Authors.
About
Create an array containing pseudorandom numbers drawn from an exponential distribution.
github.com/stdlib-js/stdlib
Topics
continuousexpexponentialgeneratorjavascriptmathmathematicsnodenode-jsnodejsprngpseudorandomrandrandomrngseedseedablestatisticsstatsstdlib
Resources
Readme
Apache-2.0 license
Code of conduct
Code of conduct
Contributing
Contributing
Security policy
Security policy
Activity
Custom properties
Stars
1 star
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Sponsor this project
Packages
Used by
Contributors
Languages

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GitHub - stdlib-js/random-array-exponential: Create an array containing pseudorandom numbers drawn from an exponential distribution. · GitHub
Skip to content
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About stdlib...

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.
The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.
When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.
To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!
Exponential Random Numbers
NPM versionBuild StatusCoverage Status
Create an array containing pseudorandom numbers drawn from an exponential distribution.
Installation
npm install @stdlib/random-array-exponential
Alternatively,
  • To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
  • If you are using Deno, visit the deno branch (see README for usage intructions).
  • For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).
The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.
To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.
Usage
varexponential=require('@stdlib/random-array-exponential');
exponential( len, lambda[, options] )
Returns an array containing pseudorandom numbers drawn from an exponential distribution.
varout=exponential(10,2.0);// returns <Float64Array>
The function has the following parameters:
  • len: output array length.
  • lambda: rate parameter.
  • options: function options.
The function accepts the following options:
By default, the function returns a Float64Array. To return an array having a different data type, set the dtype option.
varopts={'dtype': 'generic'};varout=exponential(10,2.0,opts);// returns [...]
exponential.assign( lambda, out )
Fills an array with pseudorandom numbers drawn from an exponential distribution.
varzeros=require('@stdlib/array-zeros');varx=zeros(10,'float64');// returns <Float64Array>varout=exponential.assign(2.0,x);// returns <Float64Array>varbool=(out===x);// returns true
The function has the following parameters:
  • lambda: rate parameter.
  • out: output array.
exponential.factory( [lambda, ][options] )
Returns a function for creating arrays containing pseudorandom numbers drawn from an exponential distribution.
varrandom=exponential.factory();varout=random(10,2.0);// returns <Float64Array>varlen=out.length;// returns 10
If provided lambda, the returned generator returns random variates from the specified distribution.
varrandom=exponential.factory(2.0);varout=random(10);// returns <Float64Array>out=random(10);// returns <Float64Array>
If not provided lambda, the returned generator requires that lambda be provided at each invocation.
varrandom=exponential.factory();varout=random(10,2.0);// returns <Float64Array>out=random(10,2.0);// returns <Float64Array>
The function accepts the following options:
  • prng: pseudorandom number generator for generating uniformly distributed pseudorandom numbers on the interval [0,1). If provided, the function ignores both the state and seed options. In order to seed the underlying pseudorandom number generator, one must seed the provided prng (assuming the provided prng is seedable).
  • seed: pseudorandom number generator seed.
  • state: a Uint32Array containing pseudorandom number generator state. If provided, the function ignores the seed option.
  • copy: boolean indicating whether to copy a provided pseudorandom number generator state. Setting this option to false allows sharing state between two or more pseudorandom number generators. Setting this option to true ensures that an underlying generator has exclusive control over its internal state. Default: true.
  • dtype: default output array data type. Must be a real-valued floating-point data type or "generic". Default: 'float64'.
To use a custom PRNG as the underlying source of uniformly distributed pseudorandom numbers, set the prng option.
varminstd=require('@stdlib/random-base-minstd');varopts={'prng': minstd.normalized};varrandom=exponential.factory(2.0,opts);varout=random(10);// returns <Float64Array>
To seed the underlying pseudorandom number generator, set the seed option.
varopts={'seed': 12345};varrandom=exponential.factory(2.0,opts);varout=random(10,opts);// returns <Float64Array>
The returned function accepts the following options:
To override the default output array data type, set the dtype option.
varrandom=exponential.factory(2.0);varout=random(10);// returns <Float64Array>varopts={'dtype': 'generic'};out=random(10,opts);// returns [...]
exponential.PRNG
The underlying pseudorandom number generator.
varprng=exponential.PRNG;// returns <Function>
exponential.seed
The value used to seed the underlying pseudorandom number generator.
varseed=exponential.seed;// returns <Uint32Array>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varseed=random.seed;// returns null
exponential.seedLength
Length of underlying pseudorandom number generator seed.
varlen=exponential.seedLength;// returns <number>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varlen=random.seedLength;// returns null
exponential.state
Writable property for getting and setting the underlying pseudorandom number generator state.
varstate=exponential.state;// returns <Uint32Array>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varstate=random.state;// returns null
exponential.stateLength
Length of underlying pseudorandom number generator state.
varlen=exponential.stateLength;// returns <number>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varlen=random.stateLength;// returns null
exponential.byteLength
Size (in bytes) of underlying pseudorandom number generator state.
varsz=exponential.byteLength;// returns <number>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varsz=random.byteLength;// returns null
Notes
  • If PRNG state is "shared" (meaning a state array was provided during function creation and not copied) and one sets the underlying generator state to a state array having a different length, the function returned by the factory method does not update the existing shared state and, instead, points to the newly provided state array. In order to synchronize the output of the underlying generator according to the new shared state array, the state array for each relevant creation function and/or PRNG must be explicitly set.
  • If PRNG state is "shared" and one sets the underlying generator state to a state array of the same length, the PRNG state is updated (along with the state of all other creation functions and/or PRNGs sharing the PRNG's state array).
Examples
varlogEach=require('@stdlib/console-log-each');varexponential=require('@stdlib/random-array-exponential');// Create a function for generating random arrays originating from the same state:varrandom=exponential.factory(2.0,{'state': exponential.state,'copy': true});// Generate 3 arrays:varx1=random(5);varx2=random(5);varx3=random(5);// Print the contents:logEach('%f, %f, %f',x1,x2,x3);// Create another function for generating random arrays with the original state:random=exponential.factory(2.0,{'state': exponential.state,'copy': true});// Generate a single array which replicates the above pseudorandom number generation sequence:varx4=random(15);// Print the contents:logEach('%f',x4);
See Also
Notice
This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
Community
Chat
License
See LICENSE.
Copyright
Copyright © 2016-2026. The Stdlib Authors.
About
Create an array containing pseudorandom numbers drawn from an exponential distribution.
github.com/stdlib-js/stdlib
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continuousexpexponentialgeneratorjavascriptmathmathematicsnodenode-jsnodejsprngpseudorandomrandrandomrngseedseedablestatisticsstatsstdlib
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Apache-2.0 license
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GitHub - stdlib-js/random-array-exponential: Create an array containing pseudorandom numbers drawn from an exponential distribution. · GitHub
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About stdlib...

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.
The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.
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To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!
Exponential Random Numbers
NPM versionBuild StatusCoverage Status
Create an array containing pseudorandom numbers drawn from an exponential distribution.
Installation
npm install @stdlib/random-array-exponential
Alternatively,
  • To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
  • If you are using Deno, visit the deno branch (see README for usage intructions).
  • For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).
The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.
To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.
Usage
varexponential=require('@stdlib/random-array-exponential');
exponential( len, lambda[, options] )
Returns an array containing pseudorandom numbers drawn from an exponential distribution.
varout=exponential(10,2.0);// returns <Float64Array>
The function has the following parameters:
  • len: output array length.
  • lambda: rate parameter.
  • options: function options.
The function accepts the following options:
By default, the function returns a Float64Array. To return an array having a different data type, set the dtype option.
varopts={'dtype': 'generic'};varout=exponential(10,2.0,opts);// returns [...]
exponential.assign( lambda, out )
Fills an array with pseudorandom numbers drawn from an exponential distribution.
varzeros=require('@stdlib/array-zeros');varx=zeros(10,'float64');// returns <Float64Array>varout=exponential.assign(2.0,x);// returns <Float64Array>varbool=(out===x);// returns true
The function has the following parameters:
  • lambda: rate parameter.
  • out: output array.
exponential.factory( [lambda, ][options] )
Returns a function for creating arrays containing pseudorandom numbers drawn from an exponential distribution.
varrandom=exponential.factory();varout=random(10,2.0);// returns <Float64Array>varlen=out.length;// returns 10
If provided lambda, the returned generator returns random variates from the specified distribution.
varrandom=exponential.factory(2.0);varout=random(10);// returns <Float64Array>out=random(10);// returns <Float64Array>
If not provided lambda, the returned generator requires that lambda be provided at each invocation.
varrandom=exponential.factory();varout=random(10,2.0);// returns <Float64Array>out=random(10,2.0);// returns <Float64Array>
The function accepts the following options:
  • prng: pseudorandom number generator for generating uniformly distributed pseudorandom numbers on the interval [0,1). If provided, the function ignores both the state and seed options. In order to seed the underlying pseudorandom number generator, one must seed the provided prng (assuming the provided prng is seedable).
  • seed: pseudorandom number generator seed.
  • state: a Uint32Array containing pseudorandom number generator state. If provided, the function ignores the seed option.
  • copy: boolean indicating whether to copy a provided pseudorandom number generator state. Setting this option to false allows sharing state between two or more pseudorandom number generators. Setting this option to true ensures that an underlying generator has exclusive control over its internal state. Default: true.
  • dtype: default output array data type. Must be a real-valued floating-point data type or "generic". Default: 'float64'.
To use a custom PRNG as the underlying source of uniformly distributed pseudorandom numbers, set the prng option.
varminstd=require('@stdlib/random-base-minstd');varopts={'prng': minstd.normalized};varrandom=exponential.factory(2.0,opts);varout=random(10);// returns <Float64Array>
To seed the underlying pseudorandom number generator, set the seed option.
varopts={'seed': 12345};varrandom=exponential.factory(2.0,opts);varout=random(10,opts);// returns <Float64Array>
The returned function accepts the following options:
To override the default output array data type, set the dtype option.
varrandom=exponential.factory(2.0);varout=random(10);// returns <Float64Array>varopts={'dtype': 'generic'};out=random(10,opts);// returns [...]
exponential.PRNG
The underlying pseudorandom number generator.
varprng=exponential.PRNG;// returns <Function>
exponential.seed
The value used to seed the underlying pseudorandom number generator.
varseed=exponential.seed;// returns <Uint32Array>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varseed=random.seed;// returns null
exponential.seedLength
Length of underlying pseudorandom number generator seed.
varlen=exponential.seedLength;// returns <number>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varlen=random.seedLength;// returns null
exponential.state
Writable property for getting and setting the underlying pseudorandom number generator state.
varstate=exponential.state;// returns <Uint32Array>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varstate=random.state;// returns null
exponential.stateLength
Length of underlying pseudorandom number generator state.
varlen=exponential.stateLength;// returns <number>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varlen=random.stateLength;// returns null
exponential.byteLength
Size (in bytes) of underlying pseudorandom number generator state.
varsz=exponential.byteLength;// returns <number>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varsz=random.byteLength;// returns null
Notes
  • If PRNG state is "shared" (meaning a state array was provided during function creation and not copied) and one sets the underlying generator state to a state array having a different length, the function returned by the factory method does not update the existing shared state and, instead, points to the newly provided state array. In order to synchronize the output of the underlying generator according to the new shared state array, the state array for each relevant creation function and/or PRNG must be explicitly set.
  • If PRNG state is "shared" and one sets the underlying generator state to a state array of the same length, the PRNG state is updated (along with the state of all other creation functions and/or PRNGs sharing the PRNG's state array).
Examples
varlogEach=require('@stdlib/console-log-each');varexponential=require('@stdlib/random-array-exponential');// Create a function for generating random arrays originating from the same state:varrandom=exponential.factory(2.0,{'state': exponential.state,'copy': true});// Generate 3 arrays:varx1=random(5);varx2=random(5);varx3=random(5);// Print the contents:logEach('%f, %f, %f',x1,x2,x3);// Create another function for generating random arrays with the original state:random=exponential.factory(2.0,{'state': exponential.state,'copy': true});// Generate a single array which replicates the above pseudorandom number generation sequence:varx4=random(15);// Print the contents:logEach('%f',x4);
See Also
Notice
This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
Community
Chat
License
See LICENSE.
Copyright
Copyright © 2016-2026. The Stdlib Authors.
About
Create an array containing pseudorandom numbers drawn from an exponential distribution.
github.com/stdlib-js/stdlib
Topics
continuousexpexponentialgeneratorjavascriptmathmathematicsnodenode-jsnodejsprngpseudorandomrandrandomrngseedseedablestatisticsstatsstdlib
Resources
Readme
Apache-2.0 license
Code of conduct
Code of conduct
Contributing
Contributing
Security policy
Security policy
Activity
Custom properties
Stars
1 star
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Sponsor this project
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Used by
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GitHub - stdlib-js/random-array-exponential: Create an array containing pseudorandom numbers drawn from an exponential distribution. · GitHub
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About stdlib...

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.
The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.
When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.
To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!
Exponential Random Numbers
NPM versionBuild StatusCoverage Status
Create an array containing pseudorandom numbers drawn from an exponential distribution.
Installation
npm install @stdlib/random-array-exponential
Alternatively,
  • To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
  • If you are using Deno, visit the deno branch (see README for usage intructions).
  • For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).
The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.
To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.
Usage
varexponential=require('@stdlib/random-array-exponential');
exponential( len, lambda[, options] )
Returns an array containing pseudorandom numbers drawn from an exponential distribution.
varout=exponential(10,2.0);// returns <Float64Array>
The function has the following parameters:
  • len: output array length.
  • lambda: rate parameter.
  • options: function options.
The function accepts the following options:
By default, the function returns a Float64Array. To return an array having a different data type, set the dtype option.
varopts={'dtype': 'generic'};varout=exponential(10,2.0,opts);// returns [...]
exponential.assign( lambda, out )
Fills an array with pseudorandom numbers drawn from an exponential distribution.
varzeros=require('@stdlib/array-zeros');varx=zeros(10,'float64');// returns <Float64Array>varout=exponential.assign(2.0,x);// returns <Float64Array>varbool=(out===x);// returns true
The function has the following parameters:
  • lambda: rate parameter.
  • out: output array.
exponential.factory( [lambda, ][options] )
Returns a function for creating arrays containing pseudorandom numbers drawn from an exponential distribution.
varrandom=exponential.factory();varout=random(10,2.0);// returns <Float64Array>varlen=out.length;// returns 10
If provided lambda, the returned generator returns random variates from the specified distribution.
varrandom=exponential.factory(2.0);varout=random(10);// returns <Float64Array>out=random(10);// returns <Float64Array>
If not provided lambda, the returned generator requires that lambda be provided at each invocation.
varrandom=exponential.factory();varout=random(10,2.0);// returns <Float64Array>out=random(10,2.0);// returns <Float64Array>
The function accepts the following options:
  • prng: pseudorandom number generator for generating uniformly distributed pseudorandom numbers on the interval [0,1). If provided, the function ignores both the state and seed options. In order to seed the underlying pseudorandom number generator, one must seed the provided prng (assuming the provided prng is seedable).
  • seed: pseudorandom number generator seed.
  • state: a Uint32Array containing pseudorandom number generator state. If provided, the function ignores the seed option.
  • copy: boolean indicating whether to copy a provided pseudorandom number generator state. Setting this option to false allows sharing state between two or more pseudorandom number generators. Setting this option to true ensures that an underlying generator has exclusive control over its internal state. Default: true.
  • dtype: default output array data type. Must be a real-valued floating-point data type or "generic". Default: 'float64'.
To use a custom PRNG as the underlying source of uniformly distributed pseudorandom numbers, set the prng option.
varminstd=require('@stdlib/random-base-minstd');varopts={'prng': minstd.normalized};varrandom=exponential.factory(2.0,opts);varout=random(10);// returns <Float64Array>
To seed the underlying pseudorandom number generator, set the seed option.
varopts={'seed': 12345};varrandom=exponential.factory(2.0,opts);varout=random(10,opts);// returns <Float64Array>
The returned function accepts the following options:
To override the default output array data type, set the dtype option.
varrandom=exponential.factory(2.0);varout=random(10);// returns <Float64Array>varopts={'dtype': 'generic'};out=random(10,opts);// returns [...]
exponential.PRNG
The underlying pseudorandom number generator.
varprng=exponential.PRNG;// returns <Function>
exponential.seed
The value used to seed the underlying pseudorandom number generator.
varseed=exponential.seed;// returns <Uint32Array>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varseed=random.seed;// returns null
exponential.seedLength
Length of underlying pseudorandom number generator seed.
varlen=exponential.seedLength;// returns <number>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varlen=random.seedLength;// returns null
exponential.state
Writable property for getting and setting the underlying pseudorandom number generator state.
varstate=exponential.state;// returns <Uint32Array>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varstate=random.state;// returns null
exponential.stateLength
Length of underlying pseudorandom number generator state.
varlen=exponential.stateLength;// returns <number>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varlen=random.stateLength;// returns null
exponential.byteLength
Size (in bytes) of underlying pseudorandom number generator state.
varsz=exponential.byteLength;// returns <number>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varsz=random.byteLength;// returns null
Notes
  • If PRNG state is "shared" (meaning a state array was provided during function creation and not copied) and one sets the underlying generator state to a state array having a different length, the function returned by the factory method does not update the existing shared state and, instead, points to the newly provided state array. In order to synchronize the output of the underlying generator according to the new shared state array, the state array for each relevant creation function and/or PRNG must be explicitly set.
  • If PRNG state is "shared" and one sets the underlying generator state to a state array of the same length, the PRNG state is updated (along with the state of all other creation functions and/or PRNGs sharing the PRNG's state array).
Examples
varlogEach=require('@stdlib/console-log-each');varexponential=require('@stdlib/random-array-exponential');// Create a function for generating random arrays originating from the same state:varrandom=exponential.factory(2.0,{'state': exponential.state,'copy': true});// Generate 3 arrays:varx1=random(5);varx2=random(5);varx3=random(5);// Print the contents:logEach('%f, %f, %f',x1,x2,x3);// Create another function for generating random arrays with the original state:random=exponential.factory(2.0,{'state': exponential.state,'copy': true});// Generate a single array which replicates the above pseudorandom number generation sequence:varx4=random(15);// Print the contents:logEach('%f',x4);
See Also
Notice
This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
Community
Chat
License
See LICENSE.
Copyright
Copyright © 2016-2026. The Stdlib Authors.
About
Create an array containing pseudorandom numbers drawn from an exponential distribution.
github.com/stdlib-js/stdlib
Topics
continuousexpexponentialgeneratorjavascriptmathmathematicsnodenode-jsnodejsprngpseudorandomrandrandomrngseedseedablestatisticsstatsstdlib
Resources
Readme
Apache-2.0 license
Code of conduct
Code of conduct
Contributing
Contributing
Security policy
Security policy
Activity
Custom properties
Stars
1 star
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Sponsor this project
Packages
Used by
Contributors
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GitHub - stdlib-js/random-array-exponential: Create an array containing pseudorandom numbers drawn from an exponential distribution. · GitHub
Skip to content
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Repository files navigation

About stdlib...

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.
The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.
When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.
To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!
Exponential Random Numbers
NPM versionBuild StatusCoverage Status
Create an array containing pseudorandom numbers drawn from an exponential distribution.
Installation
npm install @stdlib/random-array-exponential
Alternatively,
  • To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
  • If you are using Deno, visit the deno branch (see README for usage intructions).
  • For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).
The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.
To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.
Usage
varexponential=require('@stdlib/random-array-exponential');
exponential( len, lambda[, options] )
Returns an array containing pseudorandom numbers drawn from an exponential distribution.
varout=exponential(10,2.0);// returns <Float64Array>
The function has the following parameters:
  • len: output array length.
  • lambda: rate parameter.
  • options: function options.
The function accepts the following options:
By default, the function returns a Float64Array. To return an array having a different data type, set the dtype option.
varopts={'dtype': 'generic'};varout=exponential(10,2.0,opts);// returns [...]
exponential.assign( lambda, out )
Fills an array with pseudorandom numbers drawn from an exponential distribution.
varzeros=require('@stdlib/array-zeros');varx=zeros(10,'float64');// returns <Float64Array>varout=exponential.assign(2.0,x);// returns <Float64Array>varbool=(out===x);// returns true
The function has the following parameters:
  • lambda: rate parameter.
  • out: output array.
exponential.factory( [lambda, ][options] )
Returns a function for creating arrays containing pseudorandom numbers drawn from an exponential distribution.
varrandom=exponential.factory();varout=random(10,2.0);// returns <Float64Array>varlen=out.length;// returns 10
If provided lambda, the returned generator returns random variates from the specified distribution.
varrandom=exponential.factory(2.0);varout=random(10);// returns <Float64Array>out=random(10);// returns <Float64Array>
If not provided lambda, the returned generator requires that lambda be provided at each invocation.
varrandom=exponential.factory();varout=random(10,2.0);// returns <Float64Array>out=random(10,2.0);// returns <Float64Array>
The function accepts the following options:
  • prng: pseudorandom number generator for generating uniformly distributed pseudorandom numbers on the interval [0,1). If provided, the function ignores both the state and seed options. In order to seed the underlying pseudorandom number generator, one must seed the provided prng (assuming the provided prng is seedable).
  • seed: pseudorandom number generator seed.
  • state: a Uint32Array containing pseudorandom number generator state. If provided, the function ignores the seed option.
  • copy: boolean indicating whether to copy a provided pseudorandom number generator state. Setting this option to false allows sharing state between two or more pseudorandom number generators. Setting this option to true ensures that an underlying generator has exclusive control over its internal state. Default: true.
  • dtype: default output array data type. Must be a real-valued floating-point data type or "generic". Default: 'float64'.
To use a custom PRNG as the underlying source of uniformly distributed pseudorandom numbers, set the prng option.
varminstd=require('@stdlib/random-base-minstd');varopts={'prng': minstd.normalized};varrandom=exponential.factory(2.0,opts);varout=random(10);// returns <Float64Array>
To seed the underlying pseudorandom number generator, set the seed option.
varopts={'seed': 12345};varrandom=exponential.factory(2.0,opts);varout=random(10,opts);// returns <Float64Array>
The returned function accepts the following options:
To override the default output array data type, set the dtype option.
varrandom=exponential.factory(2.0);varout=random(10);// returns <Float64Array>varopts={'dtype': 'generic'};out=random(10,opts);// returns [...]
exponential.PRNG
The underlying pseudorandom number generator.
varprng=exponential.PRNG;// returns <Function>
exponential.seed
The value used to seed the underlying pseudorandom number generator.
varseed=exponential.seed;// returns <Uint32Array>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varseed=random.seed;// returns null
exponential.seedLength
Length of underlying pseudorandom number generator seed.
varlen=exponential.seedLength;// returns <number>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varlen=random.seedLength;// returns null
exponential.state
Writable property for getting and setting the underlying pseudorandom number generator state.
varstate=exponential.state;// returns <Uint32Array>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varstate=random.state;// returns null
exponential.stateLength
Length of underlying pseudorandom number generator state.
varlen=exponential.stateLength;// returns <number>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varlen=random.stateLength;// returns null
exponential.byteLength
Size (in bytes) of underlying pseudorandom number generator state.
varsz=exponential.byteLength;// returns <number>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varsz=random.byteLength;// returns null
Notes
  • If PRNG state is "shared" (meaning a state array was provided during function creation and not copied) and one sets the underlying generator state to a state array having a different length, the function returned by the factory method does not update the existing shared state and, instead, points to the newly provided state array. In order to synchronize the output of the underlying generator according to the new shared state array, the state array for each relevant creation function and/or PRNG must be explicitly set.
  • If PRNG state is "shared" and one sets the underlying generator state to a state array of the same length, the PRNG state is updated (along with the state of all other creation functions and/or PRNGs sharing the PRNG's state array).
Examples
varlogEach=require('@stdlib/console-log-each');varexponential=require('@stdlib/random-array-exponential');// Create a function for generating random arrays originating from the same state:varrandom=exponential.factory(2.0,{'state': exponential.state,'copy': true});// Generate 3 arrays:varx1=random(5);varx2=random(5);varx3=random(5);// Print the contents:logEach('%f, %f, %f',x1,x2,x3);// Create another function for generating random arrays with the original state:random=exponential.factory(2.0,{'state': exponential.state,'copy': true});// Generate a single array which replicates the above pseudorandom number generation sequence:varx4=random(15);// Print the contents:logEach('%f',x4);
See Also
Notice
This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
Community
Chat
License
See LICENSE.
Copyright
Copyright © 2016-2026. The Stdlib Authors.
About
Create an array containing pseudorandom numbers drawn from an exponential distribution.
github.com/stdlib-js/stdlib
Topics
continuousexpexponentialgeneratorjavascriptmathmathematicsnodenode-jsnodejsprngpseudorandomrandrandomrngseedseedablestatisticsstatsstdlib
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GitHub - stdlib-js/random-array-exponential: Create an array containing pseudorandom numbers drawn from an exponential distribution. · GitHub
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About stdlib...

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.
The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.
When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.
To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!
Exponential Random Numbers
NPM versionBuild StatusCoverage Status
Create an array containing pseudorandom numbers drawn from an exponential distribution.
Installation
npm install @stdlib/random-array-exponential
Alternatively,
  • To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
  • If you are using Deno, visit the deno branch (see README for usage intructions).
  • For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).
The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.
To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.
Usage
varexponential=require('@stdlib/random-array-exponential');
exponential( len, lambda[, options] )
Returns an array containing pseudorandom numbers drawn from an exponential distribution.
varout=exponential(10,2.0);// returns <Float64Array>
The function has the following parameters:
  • len: output array length.
  • lambda: rate parameter.
  • options: function options.
The function accepts the following options:
By default, the function returns a Float64Array. To return an array having a different data type, set the dtype option.
varopts={'dtype': 'generic'};varout=exponential(10,2.0,opts);// returns [...]
exponential.assign( lambda, out )
Fills an array with pseudorandom numbers drawn from an exponential distribution.
varzeros=require('@stdlib/array-zeros');varx=zeros(10,'float64');// returns <Float64Array>varout=exponential.assign(2.0,x);// returns <Float64Array>varbool=(out===x);// returns true
The function has the following parameters:
  • lambda: rate parameter.
  • out: output array.
exponential.factory( [lambda, ][options] )
Returns a function for creating arrays containing pseudorandom numbers drawn from an exponential distribution.
varrandom=exponential.factory();varout=random(10,2.0);// returns <Float64Array>varlen=out.length;// returns 10
If provided lambda, the returned generator returns random variates from the specified distribution.
varrandom=exponential.factory(2.0);varout=random(10);// returns <Float64Array>out=random(10);// returns <Float64Array>
If not provided lambda, the returned generator requires that lambda be provided at each invocation.
varrandom=exponential.factory();varout=random(10,2.0);// returns <Float64Array>out=random(10,2.0);// returns <Float64Array>
The function accepts the following options:
  • prng: pseudorandom number generator for generating uniformly distributed pseudorandom numbers on the interval [0,1). If provided, the function ignores both the state and seed options. In order to seed the underlying pseudorandom number generator, one must seed the provided prng (assuming the provided prng is seedable).
  • seed: pseudorandom number generator seed.
  • state: a Uint32Array containing pseudorandom number generator state. If provided, the function ignores the seed option.
  • copy: boolean indicating whether to copy a provided pseudorandom number generator state. Setting this option to false allows sharing state between two or more pseudorandom number generators. Setting this option to true ensures that an underlying generator has exclusive control over its internal state. Default: true.
  • dtype: default output array data type. Must be a real-valued floating-point data type or "generic". Default: 'float64'.
To use a custom PRNG as the underlying source of uniformly distributed pseudorandom numbers, set the prng option.
varminstd=require('@stdlib/random-base-minstd');varopts={'prng': minstd.normalized};varrandom=exponential.factory(2.0,opts);varout=random(10);// returns <Float64Array>
To seed the underlying pseudorandom number generator, set the seed option.
varopts={'seed': 12345};varrandom=exponential.factory(2.0,opts);varout=random(10,opts);// returns <Float64Array>
The returned function accepts the following options:
To override the default output array data type, set the dtype option.
varrandom=exponential.factory(2.0);varout=random(10);// returns <Float64Array>varopts={'dtype': 'generic'};out=random(10,opts);// returns [...]
exponential.PRNG
The underlying pseudorandom number generator.
varprng=exponential.PRNG;// returns <Function>
exponential.seed
The value used to seed the underlying pseudorandom number generator.
varseed=exponential.seed;// returns <Uint32Array>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varseed=random.seed;// returns null
exponential.seedLength
Length of underlying pseudorandom number generator seed.
varlen=exponential.seedLength;// returns <number>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varlen=random.seedLength;// returns null
exponential.state
Writable property for getting and setting the underlying pseudorandom number generator state.
varstate=exponential.state;// returns <Uint32Array>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varstate=random.state;// returns null
exponential.stateLength
Length of underlying pseudorandom number generator state.
varlen=exponential.stateLength;// returns <number>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varlen=random.stateLength;// returns null
exponential.byteLength
Size (in bytes) of underlying pseudorandom number generator state.
varsz=exponential.byteLength;// returns <number>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varsz=random.byteLength;// returns null
Notes
  • If PRNG state is "shared" (meaning a state array was provided during function creation and not copied) and one sets the underlying generator state to a state array having a different length, the function returned by the factory method does not update the existing shared state and, instead, points to the newly provided state array. In order to synchronize the output of the underlying generator according to the new shared state array, the state array for each relevant creation function and/or PRNG must be explicitly set.
  • If PRNG state is "shared" and one sets the underlying generator state to a state array of the same length, the PRNG state is updated (along with the state of all other creation functions and/or PRNGs sharing the PRNG's state array).
Examples
varlogEach=require('@stdlib/console-log-each');varexponential=require('@stdlib/random-array-exponential');// Create a function for generating random arrays originating from the same state:varrandom=exponential.factory(2.0,{'state': exponential.state,'copy': true});// Generate 3 arrays:varx1=random(5);varx2=random(5);varx3=random(5);// Print the contents:logEach('%f, %f, %f',x1,x2,x3);// Create another function for generating random arrays with the original state:random=exponential.factory(2.0,{'state': exponential.state,'copy': true});// Generate a single array which replicates the above pseudorandom number generation sequence:varx4=random(15);// Print the contents:logEach('%f',x4);
See Also
Notice
This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
Community
Chat
License
See LICENSE.
Copyright
Copyright © 2016-2026. The Stdlib Authors.
About
Create an array containing pseudorandom numbers drawn from an exponential distribution.
github.com/stdlib-js/stdlib
Topics
continuousexpexponentialgeneratorjavascriptmathmathematicsnodenode-jsnodejsprngpseudorandomrandrandomrngseedseedablestatisticsstatsstdlib
Resources
Readme
Apache-2.0 license
Code of conduct
Code of conduct
Contributing
Contributing
Security policy
Security policy
Activity
Custom properties
Stars
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Watchers
2 watching
Forks
0 forks
Report repository
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GitHub - stdlib-js/random-array-exponential: Create an array containing pseudorandom numbers drawn from an exponential distribution. · GitHub
Skip to content
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About stdlib...

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.
The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.
When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.
To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!
Exponential Random Numbers
NPM versionBuild StatusCoverage Status
Create an array containing pseudorandom numbers drawn from an exponential distribution.
Installation
npm install @stdlib/random-array-exponential
Alternatively,
  • To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
  • If you are using Deno, visit the deno branch (see README for usage intructions).
  • For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).
The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.
To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.
Usage
varexponential=require('@stdlib/random-array-exponential');
exponential( len, lambda[, options] )
Returns an array containing pseudorandom numbers drawn from an exponential distribution.
varout=exponential(10,2.0);// returns <Float64Array>
The function has the following parameters:
  • len: output array length.
  • lambda: rate parameter.
  • options: function options.
The function accepts the following options:
By default, the function returns a Float64Array. To return an array having a different data type, set the dtype option.
varopts={'dtype': 'generic'};varout=exponential(10,2.0,opts);// returns [...]
exponential.assign( lambda, out )
Fills an array with pseudorandom numbers drawn from an exponential distribution.
varzeros=require('@stdlib/array-zeros');varx=zeros(10,'float64');// returns <Float64Array>varout=exponential.assign(2.0,x);// returns <Float64Array>varbool=(out===x);// returns true
The function has the following parameters:
  • lambda: rate parameter.
  • out: output array.
exponential.factory( [lambda, ][options] )
Returns a function for creating arrays containing pseudorandom numbers drawn from an exponential distribution.
varrandom=exponential.factory();varout=random(10,2.0);// returns <Float64Array>varlen=out.length;// returns 10
If provided lambda, the returned generator returns random variates from the specified distribution.
varrandom=exponential.factory(2.0);varout=random(10);// returns <Float64Array>out=random(10);// returns <Float64Array>
If not provided lambda, the returned generator requires that lambda be provided at each invocation.
varrandom=exponential.factory();varout=random(10,2.0);// returns <Float64Array>out=random(10,2.0);// returns <Float64Array>
The function accepts the following options:
  • prng: pseudorandom number generator for generating uniformly distributed pseudorandom numbers on the interval [0,1). If provided, the function ignores both the state and seed options. In order to seed the underlying pseudorandom number generator, one must seed the provided prng (assuming the provided prng is seedable).
  • seed: pseudorandom number generator seed.
  • state: a Uint32Array containing pseudorandom number generator state. If provided, the function ignores the seed option.
  • copy: boolean indicating whether to copy a provided pseudorandom number generator state. Setting this option to false allows sharing state between two or more pseudorandom number generators. Setting this option to true ensures that an underlying generator has exclusive control over its internal state. Default: true.
  • dtype: default output array data type. Must be a real-valued floating-point data type or "generic". Default: 'float64'.
To use a custom PRNG as the underlying source of uniformly distributed pseudorandom numbers, set the prng option.
varminstd=require('@stdlib/random-base-minstd');varopts={'prng': minstd.normalized};varrandom=exponential.factory(2.0,opts);varout=random(10);// returns <Float64Array>
To seed the underlying pseudorandom number generator, set the seed option.
varopts={'seed': 12345};varrandom=exponential.factory(2.0,opts);varout=random(10,opts);// returns <Float64Array>
The returned function accepts the following options:
To override the default output array data type, set the dtype option.
varrandom=exponential.factory(2.0);varout=random(10);// returns <Float64Array>varopts={'dtype': 'generic'};out=random(10,opts);// returns [...]
exponential.PRNG
The underlying pseudorandom number generator.
varprng=exponential.PRNG;// returns <Function>
exponential.seed
The value used to seed the underlying pseudorandom number generator.
varseed=exponential.seed;// returns <Uint32Array>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varseed=random.seed;// returns null
exponential.seedLength
Length of underlying pseudorandom number generator seed.
varlen=exponential.seedLength;// returns <number>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varlen=random.seedLength;// returns null
exponential.state
Writable property for getting and setting the underlying pseudorandom number generator state.
varstate=exponential.state;// returns <Uint32Array>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varstate=random.state;// returns null
exponential.stateLength
Length of underlying pseudorandom number generator state.
varlen=exponential.stateLength;// returns <number>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varlen=random.stateLength;// returns null
exponential.byteLength
Size (in bytes) of underlying pseudorandom number generator state.
varsz=exponential.byteLength;// returns <number>
If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.
varminstd=require('@stdlib/random-base-minstd-shuffle').normalized;varrandom=exponential.factory(2.0,{'prng': minstd});varsz=random.byteLength;// returns null
Notes
  • If PRNG state is "shared" (meaning a state array was provided during function creation and not copied) and one sets the underlying generator state to a state array having a different length, the function returned by the factory method does not update the existing shared state and, instead, points to the newly provided state array. In order to synchronize the output of the underlying generator according to the new shared state array, the state array for each relevant creation function and/or PRNG must be explicitly set.
  • If PRNG state is "shared" and one sets the underlying generator state to a state array of the same length, the PRNG state is updated (along with the state of all other creation functions and/or PRNGs sharing the PRNG's state array).
Examples
varlogEach=require('@stdlib/console-log-each');varexponential=require('@stdlib/random-array-exponential');// Create a function for generating random arrays originating from the same state:varrandom=exponential.factory(2.0,{'state': exponential.state,'copy': true});// Generate 3 arrays:varx1=random(5);varx2=random(5);varx3=random(5);// Print the contents:logEach('%f, %f, %f',x1,x2,x3);// Create another function for generating random arrays with the original state:random=exponential.factory(2.0,{'state': exponential.state,'copy': true});// Generate a single array which replicates the above pseudorandom number generation sequence:varx4=random(15);// Print the contents:logEach('%f',x4);
See Also
Notice
This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
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Copyright © 2016-2026. The Stdlib Authors.
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Create an array containing pseudorandom numbers drawn from an exponential distribution.
github.com/stdlib-js/stdlib
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continuousexpexponentialgeneratorjavascriptmathmathematicsnodenode-jsnodejsprngpseudorandomrandrandomrngseedseedablestatisticsstatsstdlib
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