mcmc.plot: Markov chains plotting

In hkevp: Spatial Extreme Value Analysis with the Hierarchical Model of Reich and Shaby (2012)

Markov chains plotting

Description

Plots of the resulting Markov chains obtained by the MCMC procedures hkevp.fit or latent.fit. May be used to assess graphically convergence of the chains.

Usage

mcmc.plot(fit, plot.spatial, mfrow)

Arguments

fit	Output from the hkevp.fit procedure.
plot.spatial	Logical indicating if the Markov chains of the sills and ranges hyperparameters should be plotted. FALSE by default.
mfrow	Optional vector of two numerical values indicating the parameter of the window plotting called by the plot(...) function.

Author(s)

Quentin Sebille

Examples

# 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)

# Markov chains plot:
mcmc.plot(fit, TRUE)

hkevp documentation built on April 18, 2023, 5:11 p.m.