R/JMposteriorb.R

In sa4khan/AFTjmr: Recurrent event analysis and joint modeling using accelerated failure time (AFT) models

posterior.b<-function(u0,stime0,y0,xalpha0,zlong0,spred0,c15=NULL,xxx15=NULL,
        phi0,rho0,kappa0,gam0=NULL,Sigma0,sigma0,
        surv.model,rand.model){
y.lden<-sum(dnorm(y0,mean=(xalpha0+zlong0%*%u0),sd=sigma0,log=TRUE))
if(rand.model=="simple"){
psi<-(1-exp(-phi0*u0[2]*stime0))*exp(-spred0-phi0*u0[1])/(phi0*u0[2])
} else{
psi0<-c15*exp(-phi0*rowSums(t(t(xxx15)*u0)))
psi<-(sum(psi0)*stime0/2)*exp(-spred0)
}
if(surv.model=="eweibull"){
logs<-log(1-exp(gam0*log1p(-exp(-(rho0*psi)^kappa0))))
}
if(surv.model=="ggamma"){
logs<-pgamma(psi^kappa0,shape=gam0,rate=rho0^kappa0,lower.tail=FALSE,log=TRUE)
}
if(surv.model=="weibull"){
logs<--(rho0*psi)^kappa0
}
if(surv.model=="llogistic"){
logs<-log(1/(1+(rho0*psi)^kappa0))
}
if(surv.model=="lnormal"){
logs<-plnorm(psi,(-log(rho0)),(1/kappa0),lower.tail = FALSE,log.p=TRUE)
}
b.lden<-den.mnorm(u0,mean=rep(0,length(u0)),sigma=Sigma0,log=TRUE)
lden<-y.lden+logs+b.lden
return(-lden)
}