DPpackage (version 1.1-6)

DPpsBF: Computes Pseudo Bayes Factors from DPpackage output

Description

This function computes Pseudo Bayes Factors from DPpackage output.

Usage

DPpsBF(...)

Arguments

...

DPpackage output objects. These have to be of the same class.

Examples

## Not run: 
#     # Respiratory Data Example
# 
#       data(indon)
#       attach(indon)
# 
#       baseage2 <- baseage**2
#       follow <- age-baseage
#       follow2 <- follow**2 
# 
#     # Prior information
# 
#       beta0 <- rep(0,9)
#       Sbeta0 <- diag(1000,9)
#       tinv <- diag(1,1)
#       prior <- list(a0=2,b0=0.1,nu0=4,tinv=tinv,
#                     mub=rep(0,1),Sb=diag(1000,1),
#                     beta0=beta0,Sbeta0=Sbeta0)
# 
#     # Initial state
#       state <- NULL
# 
#     # MCMC parameters
# 
#       nburn <- 5
#       nsave <- 100
#       nskip <- 5
#       ndisplay <- 100
#       mcmc <- list(nburn=nburn,nsave=nsave,nskip=nskip,ndisplay=ndisplay)
# 
#     # Fit the Probit model
#       fit1 <- DPglmm(fixed=infect~gender+height+cosv+sinv+xero+baseage+
#                      baseage2+follow+follow2,random=~1|id,
#                      family=binomial(probit),
#                      prior=prior,mcmc=mcmc,state=state,status=TRUE)
# 
#     # Fit the Logit model
#       fit2 <- DPglmm(fixed=infect~gender+height+cosv+sinv+xero+baseage+
#                      baseage2+follow+follow2,random=~1|id,
#                      family=binomial(logit),
#                      prior=prior,mcmc=mcmc,state=state,status=TRUE)
# 
#     # Model comparison
#       DPpsBF(fit1,fit2)
# 
# 
# ## End(Not run)