plot,est.hiddenmixedDiffusion-method {BaPreStoPro} | R Documentation |
Plot method for the estimation results of the hidden hierarchical diffusion model.
## S4 method for signature 'est.hiddenmixedDiffusion' plot(x, par.options, style = c("chains", "acf", "density", "int.phi"), par2plot, reduced = FALSE, thinning, burnIn, priorMeans = TRUE, col.priorMean = 2, lty.priorMean = 1, level = 0.05, phi, ...)
x |
est.hiddenmixedDiffusion class, created with method |
par.options |
list of options for function par() |
style |
one out of "chains", "acf", "density", "int.phi" |
par2plot |
logical vector, which parameters to be plotted, order: (μ, Ω, γ^2, σ^2, Y) |
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 |
level |
level for style = "int.phi" |
phi |
in the case of simulation study: known values for phi |
... |
optional plot parameters |
## Not run: mu <- c(10, 3, 1); Omega = c(1, 0.4, 0.01) phi <- sapply(1:3, function(i) rnorm(20, mu[i], sqrt(Omega[i]))) model <- set.to.class("hiddenmixedDiffusion", b.fun = function(phi, t, y) phi[1]-phi[2]*y, parameter = list(mu = mu, Omega = Omega, phi = phi, gamma2 = 1, sigma2 = 0.1), y0 = function(phi, t) phi[3]) data <- simulate(model, t = seq(0, 1, by = 0.02), plot.series = TRUE) est <- estimate(model, t = seq(0, 1, by = 0.02), data$Z, 1000) plot(est, burnIn = 10, thinning = 2, reduced = TRUE) plot(est, par.options = list(mar = c(5, 4.5, 4, 2) + 0.1, mfrow = c(2,1)), xlab = "iteration") plot(est, style = "acf", main = "", par2plot = c(TRUE, TRUE, rep(FALSE, 7))) plot(est, style = "density", lwd = 2, priorMean = FALSE, par2plot = c(rep(FALSE, 6), TRUE, TRUE, FALSE)) plot(est, style = "density", col.priorMean = 1, lty.priorMean = 2, main = "posterior") plot(est, style = "acf", par.options = list(), main = "", par2plot = c(rep(FALSE, 6), TRUE, TRUE)) plot(est, style = "int.phi", phi = phi, par2plot = c(TRUE, FALSE, FALSE)) ## End(Not run)