library(normalregMix)
library(ggplot2)
# produce multiple plots on a single plot
# from http://www.cookbook-r.com/Graphs/Multiple_graphs_on_one_page_(ggplot2)/
multiplot <- function(..., plotlist=NULL, file, cols=1, layout=NULL) {
library(grid)
# Make a list from the ... arguments and plotlist
plots <- c(list(...), plotlist)
numPlots = length(plots)
# If layout is NULL, then use 'cols' to determine layout
if (is.null(layout)) {
# Make the panel
# ncol: Number of columns of plots
# nrow: Number of rows needed, calculated from # of cols
layout <- matrix(seq(1, cols * ceiling(numPlots/cols)),
ncol = cols, nrow = ceiling(numPlots/cols))
}
if (numPlots==1) {
print(plots[[1]])
} else {
# Set up the page
grid.newpage()
pushViewport(viewport(layout = grid.layout(nrow(layout), ncol(layout))))
# Make each plot, in the correct location
for (i in 1:numPlots) {
# Get the i,j matrix positions of the regions that contain this subplot
matchidx <- as.data.frame(which(layout == i, arr.ind = TRUE))
print(plots[[i]], vp = viewport(layout.pos.row = matchidx$row,
layout.pos.col = matchidx$col))
}
}
}
transition.probs <- matrix(c(0.8,0.15,0.2,0.85), ncol = 2)
beta <- matrix(c(0.7,0.3), ncol = 2)
mu = c(-1,1)
beta <- matrix(c(0.3,0.2,-0.2), ncol = 1)
mu = c(-1,1)
sigma = c(0.8)
theta2 <- list(beta = beta, mu = mu, sigma = sigma,
transition.probs = transition.probs,
initial.dist = c(1,rep(0,15)))
theta <- theta2
M <- ncol(theta$transition.probs)
s <- nrow(as.matrix(theta$beta))
is.beta.switching <- (ncol(as.matrix(theta$beta)) > 1)
is.sigma.switching <- (length(theta$sigma) > 1)
is.MSM <- TRUE
n = 300
# generates data
sample <- GenerateSample(theta, n = n,
is.MSM = is.MSM)
y <- sample$y
model <- EstimateMSAR(y = y,
M = M, s = s,
is.beta.switching = is.beta.switching,
is.sigma.switching = is.sigma.switching,
is.MSM = is.MSM)
plot.actual <- DiagPlot(model, y = y) + ggtitle("MSM-AH(1) Model (Actual)") +
theme(plot.title = element_text(lineheight=.8, face="bold"))
plot.estimated <- DiagPlot(sample$msar.model, y = y) + ggtitle("MSM-AH(1) Model (Estimated)") +
theme(plot.title = element_text(lineheight=.8, face="bold"))
multiplot(plot.actual, plot.estimated, cols = 1)
(fisher.estimated <- model$fisher.estimated)
(theta.estimated <- model$theta)
new.y <- sample$y.sample + rnorm(n)
EstimateFisherInformation(theta = theta.estimated, y = new.y, y.lagged = sample$y.lagged,
z.dependent = as.matrix(rep(0,n)),
z.independent = as.matrix(rep(0,n)),
z.dependent.lagged = as.matrix(rep(0,n)),
z.independent.lagged = as.matrix(rep(0,n)),
is.MSM = TRUE)
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