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################################################################################
#
# @brief General model adequacy test using posterior predictive testing. Prior
# predictive testing can be achieved by providing samples from the prior
# instead.
#
# @date Last modified: 2012-12-17
# @author Sebastian Hoehna
# @version 1.0
# @since 2012-12-17, version 1.0
#
# @param samples list Samples from the posterior predictive distribution
# @param observation any the observed value
# @param statistic function the function computing the statistic
# @return scalar the upper quantile of observing such a value
#
################################################################################
tess.PosteriorPredictiveTest <- function(samples,observation,statistic) {
obs <- statistic(observation)
sampled_statistics <- c()
count <- 0
for ( i in 1:length(samples)) {
# compute the statistic for the i-th sample
tmp <- statistic(samples[[i]])
if ( is.finite(tmp) ) {
count <- count + 1
sampled_statistics[count] <- tmp
}
}
p <- length(sampled_statistics[sampled_statistics < obs]) / length(sampled_statistics)
return (list(samples=sampled_statistics,pvalue=p))
}
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