hypercompetent

pearson_residuals <- function(counts, theta = 100) {
  counts_sum0 <- as(matrix(Matrix::colSums(counts),nrow=1),"dgCMatrix")
  counts_sum1 <- as(matrix(Matrix::rowSums(counts),ncol=1),"dgCMatrix")
  counts_sum <- sum(counts@x)
  
  #get residuals
  mu <- (counts_sum1 %*% counts_sum0) / counts_sum
  z <- (counts - mu) / sqrt(mu + mu^2/theta)
  
  #clip to sqrt(n)

hypercompetent

library(reshape2)
library(ggplot2)

df <- melt(volcano[20:44,10:34])

names(df) <- c("x","y","val")

rect <- data.frame(st = 5, en = 20)

ggplot() +

hypercompetent

rcau <- function() {
  angle <- 2 * pi * runif(1)
  radius <- 1 * (runif(1) ^ (1/2))
  
  x <- radius * cos(angle)
  y <- radius * sin(angle)
  
  c(x, y)
}