Bayesian Generalized Linear models using `@formula` syntax.
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Updated
Jul 4, 2024 - Julia
Bayesian Generalized Linear models using `@formula` syntax.
BayesBase is a package that serves as an umbrella, defining, exporting, and re-exporting methods essential for Bayesian statistics
Bayesian inference with probabilistic programming.
A Bayesian Analysis Toolkit in Julia
Julia package to perform Bayesian clustering of high-dimensional Euclidean data using pairwise dissimilarity information.
Bayesian Statistics using Julia and Turing
Statistical analyses for Bayesian workflows
Probabilistic programming via source rewriting
Metric Gaussian Variational Inference
Toolkit functions and example outputs for Bayesian (Structural) Vector Autoregressive (VAR) models
Transformations to contrained variables from ℝⁿ.
Implementation of robust dynamic Hamiltonian Monte Carlo methods (NUTS) in Julia.
Bayesian inference on wiring diagrams.
Accompanying Julia code for research paper, "System Effects in Identifying Risk-Optimal Data Requirements for Digital Twins of Structures"
Interface between Turing.jl and MonteCarloMeasurements.jl
WIP successor to Soss.jl
A Julia Package for Bayesian Nonparametric Analysis for Machine Learning
Markov Chain Monte Carlo convergence diagnostics in Julia
A flexible group comparison test based on dependent Dirichlet process
Graphical tools for Bayesian inference and posterior predictive checks.
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