toutes les options
[  bianca  ]
[ Paquet source : r-cran-mcmcpack  ]

Paquet : r-cran-mcmcpack (1.7-1-1)

Liens pour r-cran-mcmcpack

Screenshot

Télécharger le paquet source r-cran-mcmcpack :

Responsables :

Ressources externes :

Paquets similaires :

R routines for Markov chain Monte Carlo model estimation

This is a set of routines for GNU R that implement various statistical and econometric models using Markov chain Monte Carlo (MCMC) estimation, which allows "solving" models that would otherwise be intractable with traditional techniques, particularly problems in Bayesian statistics (where one or more "priors" are used as part of the estimation procedure, instead of an assumption of ignorance about the "true" point estimates), although MCMC can also be used to solve frequentist statistical problems with uninformative priors. MCMC techniques are also preferable over direct estimation in the presence of missing data.

Currently implemented are a number of ecological inference (EI) routines (for estimating individual-level attributes or behavior from aggregate data, such as electoral returns or census results), as well as models for traditional linear panel and cross-sectional data, some visualization routines for EI diagnostics, two item-response theory (or ideal-point estimation) models, metric, ordinal, and mixed-response factor analysis, and models for Gaussian (linear) and Poisson regression, logistic regression (or logit), and binary and ordinal-response probit models.

The suggested packages (r-cran-bayesm, -eco, and -mnp) contain additional models that may also be useful for those interested in this package.

Autres paquets associés à r-cran-mcmcpack

  • dépendances
  • recommandations
  • suggestions
  • enhances

Télécharger r-cran-mcmcpack

Télécharger pour toutes les architectures proposées
Architecture Taille du paquet Espace occupé une fois installé Fichiers
amd64 1 947,9 ko4 086,0 ko [liste des fichiers]
arm64 1 799,1 ko3 462,0 ko [liste des fichiers]