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ExperimentalDesign

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ExperimentalDesign provides tools for Design of Experiments in Julia, enabling the construction of designs for screening, modeling, exploration, and optimization.

Development on this package is ongoing, so expect things to change. Pull requests are more than welcome!

Check the documentation for the latest features and API, and check the examples directory for Jupyter Notebooks and code.

Current features are:

  • Designs that support categorical and continuous factors
  • Integration with StatsModels@formula
  • Full factorial designs:
    • Explicit: for small designs that fit in memory
    • Iterable: for larger designs, generates experiments on demand
  • Two-level fractional factorial designs
  • Plackett-Burman designs for screening (check the example)
  • Box-Behnken and central composite designs for response surface modeling
  • Flexible random designs using the Distributions package
  • Latin Hypercube designs using the LatinHypercubeSampling.jl package
  • Several variance-optimizing criteria

Intended features include the ones provided by R packages such as DoE.base, FrF2, and AlgDesign.

About

Design of Experiments in Julia

phrb.github.io/ExperimentalDesign.jl/dev/

Topics

design-of-experimentsexperimental-designjuliastatistical-analysisstatistics

Resources

Readme
License
Activity

Stars

32 stars

Watchers

3 watching

Forks

4 forks
Report repository

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Used by

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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ExperimentalDesign
BuildDocsTest Coverage
CICoverage Statuscodecov.io
ExperimentalDesign provides tools for Design of Experiments in Julia,
enabling the construction of designs for screening, modeling, exploration, and
optimization.
Development on this package is ongoing, so expect things to change. Pull
requests are more than welcome!
Check the documentation
for the latest features and API, and check the examples directory for
Jupyter Notebooks and code.
Current features are:
  • Designs that support categorical and continuous factors
  • Integration with StatsModels@formula
  • Full factorial designs:

    • Explicit: for small designs that fit in memory
    • Iterable: for larger designs, generates experiments on demand
  • Two-level fractional factorial designs
  • Plackett-Burman designs for screening (check the example)
  • Box-Behnken and central composite designs for response surface modeling
  • Flexible random designs using the Distributions package
  • Latin Hypercube designs using the LatinHypercubeSampling.jl package
  • Several variance-optimizing criteria
Intended features include the ones provided by R packages such as
DoE.base,
FrF2, and
AlgDesign.
About
Design of Experiments in Julia
phrb.github.io/ExperimentalDesign.jl/dev/
Topics
design-of-experimentsexperimental-designjuliastatistical-analysisstatistics
Resources
Readme
License
Activity
Stars
32 stars
Watchers
3 watching
Forks
4 forks
Report repository
Releases
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Used by
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
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ExperimentalDesign
BuildDocsTest Coverage
CICoverage Statuscodecov.io
ExperimentalDesign provides tools for Design of Experiments in Julia,
enabling the construction of designs for screening, modeling, exploration, and
optimization.
Development on this package is ongoing, so expect things to change. Pull
requests are more than welcome!
Check the documentation
for the latest features and API, and check the examples directory for
Jupyter Notebooks and code.
Current features are:
  • Designs that support categorical and continuous factors
  • Integration with StatsModels@formula
  • Full factorial designs:

    • Explicit: for small designs that fit in memory
    • Iterable: for larger designs, generates experiments on demand
  • Two-level fractional factorial designs
  • Plackett-Burman designs for screening (check the example)
  • Box-Behnken and central composite designs for response surface modeling
  • Flexible random designs using the Distributions package
  • Latin Hypercube designs using the LatinHypercubeSampling.jl package
  • Several variance-optimizing criteria
Intended features include the ones provided by R packages such as
DoE.base,
FrF2, and
AlgDesign.
About
Design of Experiments in Julia
phrb.github.io/ExperimentalDesign.jl/dev/
Topics
design-of-experimentsexperimental-designjuliastatistical-analysisstatistics
Resources
Readme
License
Activity
Stars
32 stars
Watchers
3 watching
Forks
4 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
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ExperimentalDesign
BuildDocsTest Coverage
CICoverage Statuscodecov.io
ExperimentalDesign provides tools for Design of Experiments in Julia,
enabling the construction of designs for screening, modeling, exploration, and
optimization.
Development on this package is ongoing, so expect things to change. Pull
requests are more than welcome!
Check the documentation
for the latest features and API, and check the examples directory for
Jupyter Notebooks and code.
Current features are:
  • Designs that support categorical and continuous factors
  • Integration with StatsModels@formula
  • Full factorial designs:

    • Explicit: for small designs that fit in memory
    • Iterable: for larger designs, generates experiments on demand
  • Two-level fractional factorial designs
  • Plackett-Burman designs for screening (check the example)
  • Box-Behnken and central composite designs for response surface modeling
  • Flexible random designs using the Distributions package
  • Latin Hypercube designs using the LatinHypercubeSampling.jl package
  • Several variance-optimizing criteria
Intended features include the ones provided by R packages such as
DoE.base,
FrF2, and
AlgDesign.
About
Design of Experiments in Julia
phrb.github.io/ExperimentalDesign.jl/dev/
Topics
design-of-experimentsexperimental-designjuliastatistical-analysisstatistics
Resources
Readme
License
Activity
Stars
32 stars
Watchers
3 watching
Forks
4 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
BranchesTags
Repository files navigation
ExperimentalDesign
BuildDocsTest Coverage
CICoverage Statuscodecov.io
ExperimentalDesign provides tools for Design of Experiments in Julia,
enabling the construction of designs for screening, modeling, exploration, and
optimization.
Development on this package is ongoing, so expect things to change. Pull
requests are more than welcome!
Check the documentation
for the latest features and API, and check the examples directory for
Jupyter Notebooks and code.
Current features are:
  • Designs that support categorical and continuous factors
  • Integration with StatsModels@formula
  • Full factorial designs:

    • Explicit: for small designs that fit in memory
    • Iterable: for larger designs, generates experiments on demand
  • Two-level fractional factorial designs
  • Plackett-Burman designs for screening (check the example)
  • Box-Behnken and central composite designs for response surface modeling
  • Flexible random designs using the Distributions package
  • Latin Hypercube designs using the LatinHypercubeSampling.jl package
  • Several variance-optimizing criteria
Intended features include the ones provided by R packages such as
DoE.base,
FrF2, and
AlgDesign.
About
Design of Experiments in Julia
phrb.github.io/ExperimentalDesign.jl/dev/
Topics
design-of-experimentsexperimental-designjuliastatistical-analysisstatistics
Resources
Readme
License
Activity
Stars
32 stars
Watchers
3 watching
Forks
4 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
ExperimentalDesign
BuildDocsTest Coverage
CICoverage Statuscodecov.io
ExperimentalDesign provides tools for Design of Experiments in Julia,
enabling the construction of designs for screening, modeling, exploration, and
optimization.
Development on this package is ongoing, so expect things to change. Pull
requests are more than welcome!
Check the documentation
for the latest features and API, and check the examples directory for
Jupyter Notebooks and code.
Current features are:
  • Designs that support categorical and continuous factors
  • Integration with StatsModels@formula
  • Full factorial designs:

    • Explicit: for small designs that fit in memory
    • Iterable: for larger designs, generates experiments on demand
  • Two-level fractional factorial designs
  • Plackett-Burman designs for screening (check the example)
  • Box-Behnken and central composite designs for response surface modeling
  • Flexible random designs using the Distributions package
  • Latin Hypercube designs using the LatinHypercubeSampling.jl package
  • Several variance-optimizing criteria
Intended features include the ones provided by R packages such as
DoE.base,
FrF2, and
AlgDesign.
About
Design of Experiments in Julia
phrb.github.io/ExperimentalDesign.jl/dev/
Topics
design-of-experimentsexperimental-designjuliastatistical-analysisstatistics
Resources
Readme
License
Activity
Stars
32 stars
Watchers
3 watching
Forks
4 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
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ExperimentalDesign
BuildDocsTest Coverage
CICoverage Statuscodecov.io
ExperimentalDesign provides tools for Design of Experiments in Julia,
enabling the construction of designs for screening, modeling, exploration, and
optimization.
Development on this package is ongoing, so expect things to change. Pull
requests are more than welcome!
Check the documentation
for the latest features and API, and check the examples directory for
Jupyter Notebooks and code.
Current features are:
  • Designs that support categorical and continuous factors
  • Integration with StatsModels@formula
  • Full factorial designs:

    • Explicit: for small designs that fit in memory
    • Iterable: for larger designs, generates experiments on demand
  • Two-level fractional factorial designs
  • Plackett-Burman designs for screening (check the example)
  • Box-Behnken and central composite designs for response surface modeling
  • Flexible random designs using the Distributions package
  • Latin Hypercube designs using the LatinHypercubeSampling.jl package
  • Several variance-optimizing criteria
Intended features include the ones provided by R packages such as
DoE.base,
FrF2, and
AlgDesign.
About
Design of Experiments in Julia
phrb.github.io/ExperimentalDesign.jl/dev/
Topics
design-of-experimentsexperimental-designjuliastatistical-analysisstatistics
Resources
Readme
License
Activity
Stars
32 stars
Watchers
3 watching
Forks
4 forks
Report repository
Releases
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Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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ExperimentalDesign
BuildDocsTest Coverage
CICoverage Statuscodecov.io
ExperimentalDesign provides tools for Design of Experiments in Julia,
enabling the construction of designs for screening, modeling, exploration, and
optimization.
Development on this package is ongoing, so expect things to change. Pull
requests are more than welcome!
Check the documentation
for the latest features and API, and check the examples directory for
Jupyter Notebooks and code.
Current features are:
  • Designs that support categorical and continuous factors
  • Integration with StatsModels@formula
  • Full factorial designs:

    • Explicit: for small designs that fit in memory
    • Iterable: for larger designs, generates experiments on demand
  • Two-level fractional factorial designs
  • Plackett-Burman designs for screening (check the example)
  • Box-Behnken and central composite designs for response surface modeling
  • Flexible random designs using the Distributions package
  • Latin Hypercube designs using the LatinHypercubeSampling.jl package
  • Several variance-optimizing criteria
Intended features include the ones provided by R packages such as
DoE.base,
FrF2, and
AlgDesign.
About
Design of Experiments in Julia
phrb.github.io/ExperimentalDesign.jl/dev/
Topics
design-of-experimentsexperimental-designjuliastatistical-analysisstatistics
Resources
Readme
License
Activity
Stars
32 stars
Watchers
3 watching
Forks
4 forks
Report repository
Releases
Packages
Used by
Contributors
Languages