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

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)

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

OLS (twoway clustered standard errors), Imperfect Multicollinearity (Ridge and PCA), ARMA(p,q) with Bootstrap

Python package for conducting power analysis for experiments using regression and/or clustered data.

Conjunto de modelos de Inteligência Artificial implementados para a disciplina de IA do sexto semestre do curso de CC da Unifor (2023.2)

Using OLS regression (and Ridge and Lasso to compare), we worked on a project that uses a dataset to predict housing prices based on user inputs on house details.

Implementation of Machine learning algorithms only using numpy.

Assessing the regression problem providing a linear model and a non-linear model.

Python code meant to imitate the behavior and output of the R programming language's lm function.

Linear and nonlinear regression in python

OLS regression with possibility of controlling for fixed effects and robust standard errors

Implementation of time-varying SLR using OLS estimates