Conduct one-way and multi-way anova in Julia with GLM.jl

Empirical Bayes mean estimation with nonparametric errors via order statistic regression in Julia (https://arxiv.org/abs/1911.05970)

Dynamical systems identification

Bayesian quantile regression in Julia

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Simulate multivariate distributions with arbitrary marginals.

Image analysis and stochastic processes on shape and landmark spaces.

A Julia package for building, and running Biochemical Systems Theory (BST) models

Linear mixed model genome scans for many traits

Causal forests following HTERF method and their interpretabilty

Cloudy Mountain Plot function in Julia

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Create triangular matrix of subplots showing 2D parameter samples

Implementation of the Persistent Homology Transform

Code for our AISTATS '22 paper "Sampling in Dirichlet Process Mixture Models for Clustering Streaming Data"

Dependency aware feature selection

Dyadic kernel density estimation in Julia

Differential Inequality Algorithms for Parametric ODEs

Empirical Bayes shrinkage in Julia

Effect size measures

A package for embeddings processing

Code generation for Euler-Lagrange equations.

A Julia package for probability distributions member of the Exponential family

Manifolds for the natural parameters of members of the exponential family of distributions

High Level API Finite Element Methods based on ExtendableGrids and ExtendableFEMBase

Particle filtering using the Feynman-Kac formalism

FishTank.jl creates an e-fish for you in case you feel lonely when you are coding.

A JuMP extension for conducting flexibility analysis.

A Julia package containing GNC algorithms for autonomous aerospace systems

A comprehensive QTL analysis tool by multivariate linear mixed model.

A unification of (hyper)graph model generation.

Models of gas-phase atmospheric chemistry and related processes

Implement the Kasahara-Shimotsu Test to decide number of components in Gaussian Mixture Model.

Geostatistical learning solvers for the GeoStats.jl framework

Geostatistical functions for the GeoStats.jl framework

Geospatial transforms for the GeoStats.jl framework

Computing the prior number of clusters for Gibbs-type priors.

Integrate deep neural network and reverse mode automatic differentiation into Gauss process, have fun !

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