BMAmevt (version 1.0.5)

MCpriorIntFun.nl: Generic Monte-Carlo integration under the prior distribution in the PB and NL models.

Description

Wrappers for MCpriorIntFun with argument prior=prior.pb or prior=prior.nl

Usage

MCpriorIntFun.nl(
  Nsim = 200,
  FUN = function(par, ...) {
     par
 },
  store = TRUE,
  Hpar = get("nl.Hpar"),
  show.progress = floor(seq(1, Nsim, length.out = 20)),
  Nsim.min = Nsim,
  precision = 0,
  ...
)
MCpriorIntFun.pb(
  Nsim = 200,
  Hpar = get("pb.Hpar"),
  dimData = 3,
  FUN = function(par, ...) {
     as.vector(par)
 },
  store = TRUE,
  show.progress = floor(seq(1, Nsim, length.out = 20)),
  Nsim.min = Nsim,
  precision = 0,
  ...
)

Value

The list returned by function MCpriorIntFun.

Arguments

Nsim

Maximum number of iterations

FUN

A function to be integrated. It may return a vector or an array.

store

Should the successive evaluations of FUN be stored ?

Hpar

Hyper-parameters for the PB prior (in MCpriorIntFun.pb) or the NL prior (MCpriorIntFun.nl). See pb.Hpar and nl.Hpar for the required formats.

show.progress

same as in posteriorMCMC

Nsim.min

The minimum number of iterations to be performed.

precision

The desired relative precision \(\epsilon\). See Details below.

...

Additional arguments to be passed to FUN.

dimData

Only for the PB model: The dimension of model's sample space. The PB parameter space is of dimension choose(dimData,2)+1. The NL model implemented here is restricted to three-dimensional sample spaces.

See Also

MCpriorIntFun