
DendroPy
 Referenced in 6 articles
[sw17711]
 such as data conversion and tree posterior distribution summarization, are also distributed and installed...

bsa
 Referenced in 5 articles
[sw26370]
 Dynamic Display of Changing Posterior in Bayesian Survival Analysis: The Software. We consider the problem ... estimating an unknown distribution function in the presence of censoring under the conditions that ... prior on is a mixture of Dirichlet distributions. A hyperparameter of the prior determines ... Gibbs sampling algorithm to estimate the posterior distributions of the parameters of interest is reviewed...

BayesOpt
 Referenced in 5 articles
[sw12003]
 sample efficient as it builds a posterior distribution to capture the evidence and prior knowledge...

BAS
 Referenced in 5 articles
[sw24118]
 deterministic sampling without replacement from posterior distributions. Prior distributions on coefficients are from Zellner...

LearnBayes
 Referenced in 3 articles
[sw04495]
 summarizing basic one and two parameter posterior distributions and predictive distributions. It contains MCMC algorithms ... summarizing posterior distributions defined by the user. It also contains functions for regression models, hierarchical...

DNest4
 Referenced in 3 articles
[sw25767]
 want to compute properties of the posterior distribution, describing knowledge of unknown quantities ... sampling, is a powerful tool for generating posterior samples and estimating marginal likelihoods ... complex problems including many where the posterior distribution is multimodal or has strong dependencies between...

rjmcmc
 Referenced in 4 articles
[sw21805]
 Gibbs sampling problem. Previouslycalculated posterior distributions are used to quickly estimate posterior model probabilities...

Emlk2d
 Referenced in 2 articles
[sw13516]
 done using the empirical cumulative probability distribution function. A Bayesian approach is adopted to ensure ... obtained as the mean of the posterior distribution. The posterior distribution also provides a complete ... intervals, confidence intervals measured from the posterior distribution, variance measured from the posterior distribution...

horserule
 Referenced in 4 articles
[sw27913]
 ensemble. We sample from the posterior distribution using a very efficient and easily implemented Gibbs ... gene expression data for cancer classification. The posterior sampling, prediction and graphical tools for interpreting...

Statalign
 Referenced in 4 articles
[sw16609]
 language that samples from the joint posterior distribution of phylogenies, alignments and evolutionary parameters...

BAT
 Referenced in 6 articles
[sw00067]
 This gives access to the full posterior probability distribution and enables straightforward parameter estimation, limit...

deBInfer
 Referenced in 2 articles
[sw14911]
 processes these inputs to estimate the posterior distributions of the parameters and any derived quantities ... diagnostics and the visualisation of the posterior distributions of model parameters and trajectories...

BayesGCM
 Referenced in 2 articles
[sw09077]
 WinBUGS to draw samples from the posterior distribution of the GCM’s parameters. The returned ... descriptive statistics, and graphs of the posterior distribution for each parameter of interest...

BayesBinMix
 Referenced in 3 articles
[sw19815]
 values by fitting mixtures of multivariate Bernoulli distributions with an unknown number of components ... accelerate the convergence to the target posterior distribution. Identifiability issues are addressed by implementing label...

dyPolyChord
 Referenced in 3 articles
[sw28938]
 sampling for multimodal or degenerate posterior distributions. dyPolyChord implements dynamic nested sampling using...

Biips
 Referenced in 3 articles
[sw19385]
 manner so that to approximate the posterior distribution of interest as well as the marginal...

perfectns
 Referenced in 3 articles
[sw28965]
 which simultaneously generates samples from the posterior distribution and an estimate of the Bayesian evidence...

mvdens
 Referenced in 1 article
[sw22349]
 Approximating multivariate posterior distribution functions from Monte Carlo samples for sequential Bayesian inference. An important ... possibility to do sequential inference: the posterior distribution obtained after seeing a first dataset ... samples from the posterior distribution, which is typically insufficient for accurate sequential inference. In order ... multivariate context. To approximate the posterior distribution, we can use either the apparent density based...

Mcmcpack
 Referenced in 49 articles
[sw07974]
 contains functions to perform Bayesian inference using posterior simulation for a number of statistical models ... pseudorandom number generators for statistical distributions, a general purpose Metropolis sampling algorithm, and tools...

BayesLogit
 Referenced in 44 articles
[sw09312]
 class of PólyaGamma distributions, which are constructed in detail. A variety of examples ... strategy leads to simple, effective methods for posterior inference that (1) circumvent the need ... efficient sampler for the PólyaGamma distribution, are implemented in the R package BayesLogit. Supplementary...