BayHaz (version 0.1-3)

CPPpostSample: Function to Sample Hazard Rates from CPP Posteriors

Description

A function to generate a random sample of hazard rates from the posterior distribution originated by a CPP prior through the observation of a sequence of possibly right censored times to event.

Usage

CPPpostSample(hyp, times, obs = NULL, mclen = 10, burnin = 0, thin = 1, lab = FALSE)

Arguments

hyp

list of hyperparameters (as generated by CPPpriorElicit)

times

vector of (possibly right censored) times to event

obs

vector of censoring indicators (0 = censored, 1 = exact)

mclen

requested sample size

burnin

burn-in parameter

thin

thinning parameter

lab

logical: should latent labels be returned?

Value

hyp

list of hyperparameters identifying the CPP prior that originated the posterior distribution from which the sample was extracted (copy of the input argument)

dat

dataframe with two variables (times and obs) containing the observations on which the posterior distribution is based

burnin

burn-in parameter used (copy of the input argument)

thin

thinning parameter used (copy of the input argument)

sgm

matrix with mclen rows (and hyp$F columns) containing the CPP jump-times

xi0

matrix with mclen rows (and just one column) containing the jump-sizes in the origin

csi

matrix with mclen rows (and hyp$F columns) containing the CPP jump-sizes

gam

matrix with mclen rows (and length(times) columns) containing the latent labels (NULL if lab is FALSE)

Details

A random scan (random start) Gibbs sampler (with slice sampling updating of jump-times) is used to generate a Markov chain sample of length mclen from the posterior distribution originated by hyp through the observation of times and obs; see La Rocca (2005).

The first burnin states of the Markov chain are discarded, then one every thin is kept.

If obs is NULL, it is assumed that all observations are exact (no censoring).

References

Luca La Rocca (2005). On Bayesian Nonparametric Estimation of Smooth Hazard Rates with a View to Seismic Hazard Assessment. Research Report n. 38-05, Department of Social, Cognitive and Quantitative Sciences, Reggio Emilia, Italy.

See Also

BayHaz-package, CPPevalHR, CPPplotHR, CPPpost2mcmc

Examples

# set RNG seed (for example reproducibility only)
set.seed(1234)

# select a CPP prior distribution
hypars<-CPPpriorElicit(r0 = 0.1, H = 1, T00 = 50, M00 = 2)
# load a data set
data(earthquakes)

# generate a posterior sample
post<-CPPpostSample(hypars, times = earthquakes$ti, obs = earthquakes$ob)