[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"

Additional linear models including instrumental variable and panel data models that are missing from statsmodels.

📖An interactive companion to the well-received textbook 'Introduction to Econometrics' by Stock & Watson (2015)

A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the result with a built-in dashboard.

A python library to build Model Trees with Linear Models at the leaves.

An R Port of Stata's 'margins' Command

Linear, IV and GMM Regressions With Any Number of Fixed Effects

🎓 Tidy tools for academics

📊 Methods of Applied Statistics Course Textbook Repository

Input Output Hidden Markov Model (IOHMM) in Python

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

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.

Tools for developing OLS regression models

Lp modeler written in Rust

Learned Sort: a model-enhanced sorting algorithm

Python port of "Common statistical tests are linear models" by Jonas Kristoffer Lindeløv.

Machine Learning C++

Subspace methods for MIMO system identification

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

liblinear bindings for Go