A Julia machine learning framework

Concise and beautiful algorithms written in Julia

Generalized linear models in Julia

A Julia package for multivariate statistics and data analysis (e.g. dimension reduction)

Julia implementation of Decision Tree (CART) and Random Forest algorithms

Fast Estimation of Linear Models with IV and High Dimensional Categorical Variables

Boosted trees in Julia

Julia package of loss functions for machine learning.

Journal-style regression tables

Beta Machine Learning Toolkit

A Julia package for estimating ARMA-GARCH models.

LIBSVM bindings for Julia

A collection of tools for chemometrics and machine learning written in Julia.

Neuroimaging (EEG, fMRI, pupil ...) regression analysis in Julia

Implementation of a Partial Least Squares Regressor

Publication quality regression and statistical tables

Bayesian Linear Regression in Julia

Microeconometric estimation in Julia

Fit, evaluate, and visualise generalised additive models (GAMs) in native Julia

Julia package for fitting mixed-effects models with flexible random/repeated covariance structure.