# R/plot.AR.R In aumath-advancedr2019/ACM_2019: Monte Carlo methods

#### Documented in plot.AR

```#' plot.AR
#'
#' The function plot.ARs() plots the target vs. the proposal density and the empirical vs. the theoretical density of the samples.
#'
#' @param ARsample samples created by acceptance rejection
#' @param ggplot indicates if you want to use ggplot; please note that ggplot has to be installed in this case
#'
#' @examples
#' C <- 1.6
#' lambda <- 0.5
#' f <- function(x) {x*exp(-x)}
#'
#' ARsimulation <- ARsim(f, C, 100000, rate = lambda)
#' plot(ARsimulation)
#' @export

plot.AR <- function(ARsample, ggplot = FALSE){
if(ggplot == TRUE){
x <- seq(min(ARsample\$samples),max(ARsample\$samples),0.01)
data1 <- data.frame(x = x, y = ARsample\$"proposal density"(x), z = ARsample\$"target density"(x))
data2 <- data.frame(x = ARsample\$samples)
plot1 <- ggplot2::ggplot(data1, ggplot2::aes(x)) +
ggplot2::geom_line(ggplot2::aes(y = y, colour = "proposal density")) +
ggplot2::geom_line(ggplot2::aes(y = z, colour = "target density")) +
ggplot2::ylab("proposal vs. target density") +
ggplot2::scale_colour_manual("", values = c("proposal density" ="green", "target density"="red"))
plot2 <- ggplot2::ggplot(data2, ggplot2::aes(x)) +
ggplot2::stat_density(ggplot2::aes(colour = "empirical target density"),geom="line") +
ggplot2::geom_line(data = data1, ggplot2::aes(x, y = z, colour = "theoretical target density")) +
ggplot2::ylab("empirical vs. theoretical density") +
ggplot2::scale_colour_manual("", breaks = c("empirical target density", "theoretical target density"), values = c("empirical target density" ="green", "theoretical target density"="red"))
gridExtra::grid.arrange(plot1, plot2, ncol=2)
} else {
y <- 0
if("ggplot2" %in% rownames(installed.packages()) && "gridExtra" %in% rownames(installed.packages())){
y <- menu(c("Yes", "No"), title="Do you want to use ggplot for plotting?")
}
if(y == 1){
x <- seq(min(ARsample\$samples),max(ARsample\$samples),0.01)
data1 <- data.frame(x = x, y = ARsample\$"proposal density"(x), z = ARsample\$"target density"(x))
data2 <- data.frame(x = ARsample\$samples)
plot1 <- ggplot2::ggplot(data1, ggplot2::aes(x)) +
ggplot2::geom_line(ggplot2::aes(y = y, colour = "proposal density")) +
ggplot2::geom_line(ggplot2::aes(y = z, colour = "target density")) +
ggplot2::ylab("proposal vs. target density") +
ggplot2::scale_colour_manual("", values = c("proposal density" ="green", "target density"="red"))
plot2 <- ggplot2::ggplot(data2, ggplot2::aes(x)) +
ggplot2::stat_density(ggplot2::aes(colour = "empirical target density"),geom="line") +
ggplot2::geom_line(data = data1, ggplot2::aes(x, y = z, colour = "theoretical target density")) +
ggplot2::ylab("empirical vs. theoretical density") +
ggplot2::scale_colour_manual("", breaks = c("empirical target density", "theoretical target density"), values = c("empirical target density" ="green", "theoretical target density"="red"))
gridExtra::grid.arrange(plot1, plot2, ncol=2)
} else{
par(mfrow = c(1,2))
x <- seq(min(ARsample\$samples),max(ARsample\$samples),0.01)
plot(x, ARsample\$"proposal density"(x), type = "l", main = "target vs. proposal",
xlab = "", ylab = "")
lines(x, ARsample\$"target density"(x), col = "red")
plot(density(ARsample\$samples), main = "theoretical vs empirical proposal", xlab = "", ylab = "")
lines(x, ARsample\$"target density"(x), col = "red")
par(mfrow = c(1,1))
}
}
}
```
aumath-advancedr2019/ACM_2019 documentation built on Nov. 26, 2019, 2:07 a.m.