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

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

Predicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)

A MATLAB library for sparse representation problems

OntoMaton facilitates ontology search and tagging functionalities within Google Spreadsheets.

Popular Econometrics content with code; Simple Linear Regression, Multiple Linear Regression, OLS, Event Study including Time Series Analysis, Fixed Effects and Random Effects Regressions for Panel Data, Heckman_2_Step for selection bias, Hausman Wu test for Endogeneity in Python, R, and STATA.

R package that provides estimation methods for Gravity Models

The Terminology Service Suite project is a collection of interactive widgets designed to ease the integration of terminology service functions into third-party applications.

Detecting structural breaks in time series data using statistical analysis and regression models in R.

Master Degree Coursework: Econometrics I

Set of functions to semi-automatically build and test Ordinary Least Squares (OLS) models in R in parallel.

Logic Analyzer IP Core

DeepEcon: Your one-stop Python package for econometric algorithms.

My daily ML practices

Demo UI: https://ts4nfdi.github.io/api-gateway

Comprehensive Stata do-file for testing and correcting violations of classical OLS assumptions: model specification, heteroskedasticity, multicollinearity, spatial autocorrelation, endogeneity, residual normality, and outlier/influence detection.

Stock market prediction on 5 italian companies using VAR model, OLS regressions and LSTM recurrent neural networks over data retrieved from Refinitiv Eikon

Generalized Improved Second Order RBF Neural Network with Center Selection using OLS

Apex team`s multiple regression project. It contains: What is Multiple Regression? Advantages and disadvantages of multiple regression, least square method and real implementation.