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]

Machine Learning From Scratch

Trying different regression models on Life Expectancy dataset.

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

A small Poisson regression implementation

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.

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

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