[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

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

Input Output Hidden Markov Model (IOHMM) in Python

📊 Methods of Applied Statistics Course Textbook Repository

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

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

Learned Sort: a model-enhanced sorting algorithm

Machine Learning C++

Subspace methods for MIMO system identification

Spells for everyday living. (also a book coming out in 2024)

Easy grafs, ANOVAs and posthoc comparisons.