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Stan is a probabilistic programming language for statistical inference written in C++. [2] The Stan language is used to specify a (Bayesian) statistical model with an imperative program calculating the log probability density function .
JASP – A free software alternative to IBM SPSS Statistics with additional option for Bayesian methods; JMulTi – For econometric analysis, specialised in univariate and multivariate time series analysis; Just another Gibbs sampler (JAGS) – a program for analyzing Bayesian hierarchical models using Markov chain Monte Carlo developed by ...
Download QR code; Print/export ... Pages in category "Free Bayesian statistics software" ... Stan (software) This page was ...
Stan is a probabilistic programming language for statistical inference written in C++ ArviZ a Python library for exploratory analysis of Bayesian models Bambi is a high-level Bayesian model-building interface based on PyMC
More recently, other languages to support Bayesian model specification and inference allow different or more efficient choices for the underlying Bayesian computation, and are accessible from the R data analysis and programming environment, e.g.: Stan, NIMBLE and NUTS. The influence of the BUGS language is evident in these later languages ...
Bayesian inference using Gibbs sampling (BUGS) is a statistical software for performing Bayesian inference using Markov chain Monte Carlo (MCMC) methods. It was developed by David Spiegelhalter at the Medical Research Council Biostatistics Unit in Cambridge in 1989 and released as free software in 1991.
Bayesian Analysis of Trees With Internal Node Generation: Bayesian inference, demographic history, population splits: I. J. Wilson, Weale, D.Balding BayesPhylogenies [8] Bayesian inference of trees using Markov chain Monte Carlo methods: Bayesian inference, multiple models, mixture model (auto-partitioning) M. Pagel, A. Meade BayesTraits [9]
There are a few reviews of free statistical software. There were two reviews in journals (but not peer reviewed), one by Zhu and Kuljaca [26] and another article by Grant that included mainly a brief review of R. [27] Zhu and Kuljaca outlined some useful characteristics of software, such as ease of use, having a number of statistical procedures and ability to develop new procedures.