Fast Best-Subset Selection Library
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Updated
Sep 14, 2024 - C++
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.
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
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
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