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  • Lausanne, Switzerland

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JRigh/README.md

Hey I'm Julian,

A Data Scientist from Switzerland, initially trained as a Statistician, programming mostly in the R language, also Python and others.

Skills

  • Descriptive statistics
  • Data visualization
  • Monte Carlo simulations and ressampling methods
  • Statistical modeling and inference

IT

Languages

Citizenships

  • Switzerland
  • Spain

Education

  • Bsc. Business Administration (HES-SO University of Applied Science, Fribourg, 2016)
  • Msc. Statistics (University of Neuchâtel, 2019)
  • external PhD. candidate in Statistics and scientific collaborator (University of Fribourg, ongoing as of 2022. Research area: fuzzy logic, fuzzy set theory, fuzzy statistical inference)

Affiliation

  • The Swiss Statistical Society (SSS)
  • Royal Statistical Society (RSS)

Connect with me

RRR

Tools and libraries

pythonnumpypandasscikit_learnseaborntensorflow

Rdplyrggplot2lubridatetidymodelsrsample

Please reach out for information/inquiries.

Buy Me A Coffee

Pinned Loading

  1. Poisson-Gamma-example-in-RPoisson-Gamma-example-in-RPublic

    Example of Poisson-Gamma model in Bayesian analysis in R

    R 1

  2. Data-visualization-in-RData-visualization-in-RPublic

    Some elements of data visualization with R

    Jupyter Notebook

  3. Time-series-and-Survival-analysis-in-PythonTime-series-and-Survival-analysis-in-PythonPublic

    Material from the great IBM MOOC on time series forecasting with python available through Coursera

    Jupyter Notebook 1

  4. MC-Integration-and-simulations-in-R-and-PythonMC-Integration-and-simulations-in-R-and-PythonPublic

    Monte Carlo (MC) Integration and simulations in R and Python

    Jupyter Notebook 1 1

  5. Beta-Model-Estimation-in-R-and-PythonBeta-Model-Estimation-in-R-and-PythonPublic

    Method of Moments and Maximum Likelihood estimation for a Beta model

    Jupyter Notebook 1

  6. LOOCV-Cross-validation-for-regression-in-R-and-PythonLOOCV-Cross-validation-for-regression-in-R-and-PythonPublic

    Leave-one-out Cross-validation for regression models

    R 4