ttest_MonteCarlo_example1.R

install.packages("MonteCarlo")
library(MonteCarlo)
library(dplyr)
library(ggplot2)
#Monte Carlo example from https://cran.r-project.org/web/packages/MonteCarlo/vignettes/MonteCarlo-Vignette.html
ttest <- function(n,loc,scale){
  #generate sample:
  sample <- rnorm(n,loc,scale)
  #calculate test statistic:
  stat <- sqrt(n)*mean(sample)/sd(sample)
  #get test decision:
  #decision <- abs(stat)>1.96
  #return result:
  return(list("stat"=stat))
}
#define parameter grid
n_grid <- c(50,100,250,500)
loc_grid <- seq(0,1,0.2)
scale_grid <- c(1,2)
#collect parameter grids in list:
param_list = list("n"=n_grid, "loc"=loc_grid, "scale"=scale_grid)
#run simulation:
MC_result <- MonteCarlo(func=ttest, nrep=1000, param_list=param_list)
summary(MC_result)
#generate table:
MakeTable(output=MC_result, rows="n", cols=c("loc","scale"),digits=2,include_meta=FALSE)

df <- MakeFrame(MC_result)
head(df)
tbl <- as_tibble(df)
#plot histogram of final results
ggplot(filter(tbl,loc==0,scale==1)) + geom_density(aes(x=stat, col=factor(n)))