## ----eval=FALSE, include=TRUE-------------------------------------------------
# dipNorm <- data.frame(matrix(ncol = 3, nrow =10))
# 
# for(i in 1:10){
#   dipNorm[i,1] <- 100
#   dipNorm[i,2] <- rbinom(n = 1, size = 100, prob = 0.5)
#   dipNorm[i,3] <- dipNorm[i,1] - dipNorm[i,2]
# }

## ----eval=FALSE, include=TRUE-------------------------------------------------
# dipBias <- data.frame(matrix(ncol = 3, nrow =10))
# coverage <- c(rep(100, 9), 400)
# prob <- c(rep(0.5, 9), 0.5)
# for(i in 1:10){
#   dipBias[i,1] <- coverage[i]
#   dipBias[i,2] <- rbinom(n = 1, size = coverage[i], prob = prob[i])
#   dipBias[i,3] <- dipBias[i,1] - dipBias[i,2]
# }

## ----echo=FALSE, out.width="125%", fig.align='center'-------------------------
knitr::include_graphics("../man/figures/OutlierEqualFreq.png", dpi = 5000)

## ----echo=FALSE, out.width="125%", fig.align='center'-------------------------
knitr::include_graphics("../man/figures/OutlierWithSD.png", dpi = 5000)

