Fast Best-Subset Selection Library

🎓 Tidy tools for academics

Poisson pseudo-likelihood regression with multiple levels of fixed effects

BAS R package for Bayesian Model Averaging and Variable Selection

Models for estimating football (soccer) team-strength

Fast Change Point Detection in R

A bot that provides soccer predictions using Poisson regression

Best Subset Selection algorithm for Regression, Classification, Count, Survival analysis

Quick Guide for Modelling Count Data in A Multilevel Framework

R material for LSHTM's Advanced Statistical Methods in Epidemiology (ASME) practical sessions

A 30+ node flowchart for selecting the right statistical test for evaluating experimental data.

Bayesian Statistics with R [Gibbs Sampling, Metrapolis Hastings, Regression, Logistic Regression, Poisson Regression, Multi Factor Anova, Hierarchical Modelling, Mixture Models]

Collection of end-to-end regression problems (in-depth: linear regression, logistic regression, poisson regression) 📈

Regression Models for Epidemiology

Trying different regression models on Life Expectancy dataset.

Machine Learning From Scratch

Course XCS229i in Machine Learning from Stanford University

A small Poisson regression implementation

Norm Constrained Generalised Linear Model using numpy, numba and scipy.

These are the R scripts used to calculate the model coefficients for the Android application.

This project contains the data and code used in the paper: Denter, Nils M.; Aaldering, Lukas Jan; Caferoglu, Huseyin (2022): Forecasting future bigrams and promising patents: Introducing text-based link prediction. In Foresight ahead-of-print (ahead-of-print). DOI: doi.org/10.1108/fs-03-2021-0078.

Machine Learning algorithms from-scratch implementation. It covers most Supervised and Unsupervised algorithms. Homework assignments and Projects for graduate level Machine Learning Course taught by Dr Manfred Huber at UTA during Spring 21

R package 'bpr' to perform posterior inference for Bayesian Poisson regression

The project aims at using quasi-experimental designs to estimate the impact of policy reducing speed limits in major cities, on the number of road accidents. It is based on Bayesian hierarchical modelling and Poisson regression

Regression analysis in Rust.

:hash: R, Linear Regression, Inferences, Correlation Analysis, Diagnosis, Remedial Measures,, Multiple Linear Regression, Quantitative and Qualitative Predictors, Logistic Regression and Poisson Regression, FIFA 18 Players Wages Prediction, HR Attrition at IBM Prediction. :1234:

A comparison between Poisson regression, quasi-Poisson regression, and negative binomial regression for overdispersed count data.

Generic implementation for Generalized Linear Models including Logistic, Poisson and Ordinal Regression for Classification purposes

Bayesian pliable lasso for sparse interaction effects and missing data in GLMs

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