MCpriorIntFun.pb: Generic Monte-Carlo integration under the prior distribution...

Description Usage Arguments Value See Also

View source: R/MCpriorIntFun.pb.r

Description

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

Usage

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  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, ...)

Arguments

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.

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.

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 ?

show.progress

same as in posteriorMCMC

Nsim.min

The minimum number of iterations to be performed.

precision

The desired relative precision ε. See Details below.

...

Additional arguments to be passed to FUN.

Value

The list returned by function MCpriorIntFun.

See Also

MCpriorIntFun


lbelzile/BMAmevt documentation built on May 17, 2018, 12:16 p.m.