Package: GSM 1.3.2

Sergio Venturini

GSM: Gamma Shape Mixture

Implementation of a Bayesian approach for estimating a mixture of gamma distributions in which the mixing occurs over the shape parameter. This family provides a flexible and novel approach for modeling heavy-tailed distributions, it is computationally efficient, and it only requires to specify a prior distribution for a single parameter.

Authors:Sergio Venturini

GSM_1.3.2.tar.gz
GSM_1.3.2.tar.gz(r-4.7-any)GSM_1.3.2.tar.gz(r-4.6-any)
GSM_1.3.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
GSM/json (API)

# Install 'GSM' in R:
install.packages('GSM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.41 score 26 scripts 282 downloads 40 mentions 10 exports 1 dependencies

Last updated from:053a0b3600. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK154
source / vignettesOK136
linux-release-x86_64OK153
wasm-releaseOK95

Exports:allcurves.qdgsmestim.gsmestim.gsm_thetapgsmplotpredictqgsmrgsmsummary

Dependencies:gtools

Readme and manuals

Help Manual

Help pageTopics
Estimation of a Gamma Shape Mixture ModelGSM-package
Utility Functionallcurves.q
Estimation of a Gamma Shape Mixture Model (GSM) with collapsingestim.gsm
Estimation of a Gamma Shape Mixture Model (GSM)estim.gsm_theta
Class "gsm". Result of Gamma Shape Mxiture Estimation.gsm-class initialize,gsm-method
Utility Functiondgsm GSMDist pgsm qgsm rgsm
Plot of a Gamma Shape Mixture Modelplot,ANY,ANY-method plot,gsm,missing-method plot-methods
Tail Probability Estimation for a Gamma Shape Mixture Modelpredict,ANY-method predict,gsm-method predict-methods
Summarizing Gamma Shape Mixturessummary,ANY-method summary,gsm-method summary-methods