GammaModel-class: Class '"GammaModel"'

In DPP: Inference of Parameters of Normal Distributions from a Mixture of Normals

Description

Objects of the GammaModel class are initialized with prior parameters to be used by the MCMC algorithm in dppMCMC_C class. An object of the class GammaModel will be passed as an argument upon creation of the dppMCMC_C object that will run the MCMC code.

Methods

new(GammaModel,
                    shape_prior_mean=4,
                    shape_prior_sd=1,
                    rate_prior_mean=1.5,
                    rate_prior_sd=0.54,
                    estimate_concentration_parameter=TRUE,
                    concentration_parameter_alpha=10,
                    proposal_disturbance_sd=0.1)
       instantiates a GammaModel object

getParameters()
  returns a list with the parameters and arguments supplied upon object initialization 

Examples

#creating an object of the class NormalModel
gamma.model<-new(GammaModel,
                    shape_prior_mean=4,
                    shape_prior_sd=1,
                    rate_prior_mean=1.5,
                    rate_prior_sd=0.54,
                    estimate_concentration_parameter=TRUE,
                    concentration_parameter_alpha=10,
                    proposal_disturbance_sd=0.1)
gamma.model$getParameters()

DPP documentation built on May 6, 2019, 1:10 a.m.