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.

Author
Sergio Venturini
Date of publication
2015-07-08 00:27:06
Maintainer
Sergio Venturini <sergio.venturini@unibocconi.it>
License
GPL (>= 2)
Version
1.3.2
URLs

View on CRAN

Man pages

allcurves.q
Utility Function
estim.gsm
Estimation of a Gamma Shape Mixture Model (GSM) with...
estim.gsm_theta
Estimation of a Gamma Shape Mixture Model (GSM)
gsm-class
Class "gsm". Result of Gamma Shape Mxiture Estimation.
GSMDist
Utility Function
GSM-package
Estimation of a Gamma Shape Mixture Model
plot-methods
Plot of a Gamma Shape Mixture Model
predict-methods
Tail Probability Estimation for a Gamma Shape Mixture Model
summary-methods
Summarizing Gamma Shape Mixtures

Files in this package

GSM
GSM/tests
GSM/tests/test.R
GSM/NAMESPACE
GSM/R
GSM/R/AllClasses.R
GSM/R/GSM.R
GSM/MD5
GSM/DESCRIPTION
GSM/man
GSM/man/GSMDist.Rd
GSM/man/summary-methods.Rd
GSM/man/allcurves.q.Rd
GSM/man/estim.gsm.Rd
GSM/man/gsm-class.Rd
GSM/man/estim.gsm_theta.Rd
GSM/man/plot-methods.Rd
GSM/man/predict-methods.Rd
GSM/man/GSM-package.Rd