plot-est.NHPP-method: Plot method for the Bayesian estimation results

In BaPreStoPro: Bayesian Prediction of Stochastic Processes

Description

Plot method for the estimation results of the NHPP.

Usage

## S4 method for signature 'est.NHPP'
plot(x, par.options, style = c("chains", "acf",
  "density"), par2plot, reduced = FALSE, thinning, burnIn,
  priorMeans = TRUE, col.priorMean = 2, lty.priorMean = 1, ...)

Arguments

x	est.NHPP class, created with method estimate,NHPP-method
par.options	list of options for function par()
style	one out of "chains", "acf", "density"
par2plot	logical vector, which parameters to be plotted, order: (φ, θ, γ^2, ξ, N)
reduced	logical (1), if TRUE, the chains are thinned and burn-in phase is dropped
thinning	thinning rate, if missing, the proposed one by the estimation procedure is taken
burnIn	burn-in phase, if missing, the proposed one by the estimation procedure is taken
priorMeans	logical(1), if TRUE (default), prior means are marked with a line
col.priorMean	color of the prior mean line, default 2
lty.priorMean	linetype of the prior mean line, default 1
...	optional plot parameters

Examples

model <- set.to.class("NHPP", parameter = list(xi = c(5, 1/2)),
  Lambda = function(t, xi) (t/xi[2])^xi[1])
data <- simulate(model, t = seq(0, 1, by = 0.01), plot.series = TRUE)
est <- estimate(model, t = seq(0, 1, by = 0.01), data$Times, 10000)  # nMCMC small for example
plot(est)
plot(est, burnIn = 1000, thinning = 20, reduced = TRUE)
plot(est, xlab = "iteration")
plot(est, style = "acf", main = "", par2plot = c(TRUE, FALSE), par.options = list(mfrow = c(1, 1)))
plot(est, style = "density", lwd = 2, priorMean = FALSE)
plot(est, style = "density", col.priorMean = 1, lty.priorMean = 2, main = "posterior")
plot(est, style = "acf", par.options = list(), par2plot = c(FALSE, TRUE), main = "")

BaPreStoPro documentation built on May 2, 2019, 3:34 p.m.