BaPreStoPro (version 0.1)

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

Description

Plot method for the estimation results of the NHPP.

Usage

"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: $(\phi, \theta, \gamma^2, \xi, N)$

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 = "")