Package: Ultimixt 2.1
Kaniav Kamary
Ultimixt: Bayesian Analysis of Location-Scale Mixture Models using a Weakly Informative Prior
A generic reference Bayesian analysis of unidimensional mixture distributions obtained by a location-scale parameterisation of the model is implemented. The including functions simulate and summarize posterior samples for location-scale mixture models using a weakly informative prior. There is no need to define priors for scale-location parameters except two hyperparameters in which are associated with a Dirichlet prior for weights and a simplex.
Authors:
Ultimixt_2.1.tar.gz
Ultimixt_2.1.tar.gz(r-4.5-noble)Ultimixt_2.1.tar.gz(r-4.4-noble)
Ultimixt_2.1.tgz(r-4.4-emscripten)Ultimixt_2.1.tgz(r-4.3-emscripten)
Ultimixt.pdf |Ultimixt.html✨
Ultimixt/json (API)
| # Install 'Ultimixt' in R: |
| install.packages('Ultimixt', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 8 years agofrom:adece4fe96. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 28 2024 |
| R-4.5-linux | OK | Oct 28 2024 |
Exports:K.MixPoisK.MixReparametrizedPlot.MixReparametrizedSM.MAP.MixReparametrizedSM.MixPoisSM.MixReparametrized
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| set of R functions for estimating the parameters of mixture distribution with a Bayesian non-informative prior | Ultimixt-package Ultimixt |
| Sample from a Poisson mixture posterior associated with a noninformative prior and obtained by Metropolis-within-Gibbs sampling | K.MixPois |
| Sample from a Gaussian mixture posterior associated with a noninformative prior and obtained by Metropolis-within-Gibbs sampling | K.MixReparametrized |
| plot of the MCMC output produced by K.MixReparametrized | Plot.MixReparametrized |
| summary of the output produced by K.MixReparametrized | SM.MAP.MixReparametrized |
| summary of the output produced by K.MixPois | SM.MixPois |
| summary of the output produced by K.MixReparametrized | SM.MixReparametrized |