Fast Best-Subset Selection Library

🎓 Tidy tools for academics

Poisson pseudo-likelihood regression with multiple levels of fixed effects

Models for estimating football (soccer) team-strength

A bot that provides soccer predictions using Poisson regression

FAST Change Point Detection in R

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.

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

A small Poisson regression implementation

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.

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

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

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