Autologistic regression models in Julia
OTHER License
A Julia package for robust regressions using M-estimators and quantile regressions
Simple & fast linear regression in Julia
A unified interface for simulating and evaluating sequential sampling models in Julia.
Generalized Linear Regressions Models (penalized regressions, robust regressions, ...)
Toolkit functions and example outputs for Bayesian (Structural) Vector Autoregressive (VAR) models
Bayesian Generalized Linear models using `@formula` syntax.
Graphical tools for Bayesian inference and posterior predictive checks
Algorithms for quantifying associations, independence testing and causal inference from data.
Linear Regression for Julia
Implementation of a Partial Least Squares Regressor
Implementation of robust dynamic Hamiltonian Monte Carlo methods (NUTS) in Julia.
An acausal modeling framework for automatically parallelized scientific machine learning (SciML) ...
Estimation of person parameters for item response models in Julia
A Julia package for Beta-like regression models useful for subjective scales data (Likert scales,...
Examples for Bayesian inference using DynamicHMC.jl and related packages.