mcmc.fun: Point estimates of HKEVP fit

Description Usage Arguments Details Value Author(s) Examples

View source: R/mcmc.fun.R

Description

Application of a function to the main Markov chains resulting from the procedure hkevp.fit. May be used to obtain point estimates on posterior distribution (e.g. the mean, the median). See details.

Usage

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mcmc.fun(fit, FUN, ...)

Arguments

fit

A named list. Output from the hkevp.fit procedure.

FUN

The function applied to the Markov chains in fit. The median by default. The output from FUN must be a single value.

...

Optional arguments of the function to be applied on the Markov chains (e.g. na.rm = FALSE).

Details

A function is applied to the main Markov chains resulting from the MCMC procedures hkevp.fit or latent.fit. These chains correspond to the three GEV parameters, the dependence parameter α and the bandwidth τ.

The value returned by FUN must be a single value.

Value

If fitted model is the HKEVP, a named list with three elements:

If fitted model is the latent variable model, the functions returns the GEV matrix only.

Author(s)

Quentin Sebille

Examples

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# Simulation of HKEVP:
sites <- as.matrix(expand.grid(1:3,1:3))
knots <- sites
loc <- sites[,1]*10
scale <- 3
shape <- .2
alpha <- .4
tau <- 1
ysim <- hkevp.rand(10, sites, knots, loc, scale, shape, alpha, tau)

# HKEVP fit:
fit <- hkevp.fit(ysim, sites, niter = 1000)

# Posterior median and standard deviation:
# mcmc.fun(fit, median)
# mcmc.fun(fit, sd)

hkevp documentation built on May 30, 2017, 5:21 a.m.

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