Starter code of Prof. Andrew Ng's machine learning MOOC in R statistical language

📦 BRoadly Useful Convenient and Efficient R functions that BRing Users Concise and Elegant R data analyses.

Mathematical & Statistical topics to perform statistical analysis and tests; Linear Regression, Probability Theory, Monte Carlo Simulation, Statistical Sampling, Bootstrapping, Dimensionality reduction techniques (PCA, FA, CCA), Imputation techniques, Statistical Tests (Kolmogorov Smirnov), Robust Estimators (FastMCD) and more in Python and R.

Generates and evaluates D, I, A, Alias, E, T, G, and custom optimal designs. Supports generation and evaluation of mixture and split/split-split/N-split plot designs. Includes parametric and Monte Carlo power evaluation functions. Provides a framework to evaluate power using functions provided in other packages or written by the user.

By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.

Source code repository for the R package lfe on CRAN.

This repository contains R code for exercices and plots in the famous book.

Data Science courses in R from HarvardX

Market Mix Modelling for an eCommerce firm to estimate the impact of various marketing levers on sales

🔮 Benchmarking and visualization toolkit for penalized Cox models

A series of articles to get started into the field of Machine Learning with R language

📈 Useful notes and personal collections on statistics.

FAST Change Point Detection in R

This project tries to replicate hedge funds returns.

snpnet - Efficient Lasso Solver for Large-scale genetic variant data

https://filippob.github.io/introduction_to_gwas/

Data Wrangling, Linear Models & other misc. Inferential Statistics.

🧲 Multi-step adaptive estimation for reducing false positive selection in sparse regressions

📊 Generalized linear regression models with network-regularization in R.

The project aims to perform various visualizations and provide various insights from the considered Indian automobile dataset by performing data analysis that utilizing machine learning algorithms in R programming language.