Statistics is a mathematical discipline concerned with developing and studying mathematical methods for collecting, analyzing, interpreting, and presenting large quantities of numerical data. Statistics is a highly interdisciplinary field of study with applications in fields such as physics, chemistry, life sciences, political science, and economics.
A Julia machine learning framework
A Julia package for probability distributions and associated functions.
⚡ Single-pass algorithms for statistics
Generalized linear models in Julia
Basic statistics for Julia
An extensible framework for geospatial data science and geostatistical modeling fully written in Julia
A Julia package for fitting (statistical) mixed-effects models
"Distributions" that might not add to one.
A Julia package for multivariate statistics and data analysis (e.g. dimension reduction)
Hypothesis tests for Julia
StateSpaceModels.jl is a Julia package for time-series analysis using state-space models.
A Bayesian Analysis Toolkit in Julia
Kernel density estimators for Julia
Beautiful and flexible vizualizations of high dimensional data
Convenience meta-package to load essential packages for statistics
Arrays for working with categorical data (both nominal and ordinal)
Statistical bootstrapping library for Julia
A Julia package for simulation, inference and learning of Hidden Markov Models.
Transforms and pipelines with tabular data in Julia