posteriorMean function

Posterior predictive density on the simplex, for three-dimensional extreme value models.

Computes an approximation of the posterior mean of a parameter functional, based on a posterior parameters sample.

posteriorMean(
  post.sample,
  FUN = function(par, ...) {
     par
 },
  from = NULL,
  to = NULL,
  thin = 50,
  displ = TRUE,
  ...
)

Arguments

• post.sample: A posterior sample as returned by posteriorMCMC
• FUN: a parameter functional returning a vector.
• from: Integer or NULL. If NULL, the default value is used. Otherwise, should be greater than post.sample$Nbin. Indicates the index where the averaging process should start. Default to post.sample$Nbin +1
• to: Integer or NULL. If NULL, the default value is used. Otherwise, must be lower than Nsim+1. Indicates where the averaging process should stop. Default to post.sample$Nsim.
• thin: Thinning interval.
• displ: logical. Should a plot be produced ?
• ...: Additional parameters to be passed to FUN.

Returns

A list made of

• values: A matrix : each column is the result of FUN applied to a parameter from the posterior sample.
• est.mean: The posterior mean
• est.sd: The posterior standard deviation

Details

Only a sub-sample is used: one out of thin parameters is used (thinning). Further, only the parameters produced between time from and time to (included) are kept.

See Also

posteriorMCMC.