R Under development (unstable) (2023-12-13 r85679 ucrt) -- "Unsuffered Consequences"
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> 
>  library(aster)
> 
>  do.chisq.test <- function(x, mu, max.bin) {
+      stopifnot(all(x >= 0))
+      xx <- seq(1, max.bin)
+      yy <- dpois(xx, mu)
+      yy[length(yy)] <- ppois(max.bin - 1, mu, lower.tail = FALSE)
+      pp <- yy / sum(yy)
+      ecc <- length(x) * pp
+      if (any(ecc < 5.0))
+          warning("violates rule of thumb about > 5 expected in each cell")
+      cc <- tabulate(x, max.bin)
+      chisqstat <- sum((cc - ecc)^2 / ecc)
+      pval <- pchisq(chisqstat, length(ecc) - 1, lower.tail = FALSE)
+      list(chisqstat = chisqstat, df = length(ecc) - 1, pval = pval,
+              observed = cc, expected = ecc, x = xx)
+  }
> 
>  set.seed(42)
>  nsim <- 1e4
> 
>  mu <- 2.0
>  x <- rnzp(nsim, mu)
>  chisqout1 <- do.chisq.test(x, mu, 8)
> 
>  mu <- 1.0
>  x <- rnzp(nsim, mu)
>  chisqout2 <- do.chisq.test(x, mu, 5)
> 
>  mu <- 0.5
>  x <- rnzp(nsim, mu)
>  chisqout3 <- do.chisq.test(x, mu, 4)
> 
>  nsim <- 1e6
>  mu <- 0.05
>  x <- rnzp(nsim, mu)
>  chisqout4 <- do.chisq.test(x, mu, 4)
> 
>  # nsim <- 1e7
>  # mu <- 0.005
>  # x <- rnzp(nsim, mu)
>  # do.chisq.test(x, mu, 3)
> 
>  mu <- 0.5
>  xpred <- 0:10
>  save.seed <- .Random.seed
>  x <- rnzp(xpred, mu, xpred)
>  .Random.seed <- save.seed
>  my.x <- rep(0, length(xpred))
>  for (i in seq(along = xpred))
+      if (xpred[i] > 0)
+          for (j in 1:xpred[i])
+              my.x[i] <- my.x[i] + rnzp(1, mu)
>  all.equal(x, my.x)
[1] TRUE
> 
>  foo <- new.env(parent = emptyenv())
>  bar <- suppressWarnings(try(load("nzp.rda", foo), silent = TRUE))
>  if (inherits(bar, "try-error")) {
+      save(list = paste("chisqout", 1:4, sep = ""), file = "nzp.rda")
+  } else {
+      print(all.equal(chisqout1, foo$chisqout1))
+      print(all.equal(chisqout2, foo$chisqout2))
+      print(all.equal(chisqout3, foo$chisqout3))
+      print(all.equal(chisqout4, foo$chisqout4))
+  }
[1] TRUE
[1] TRUE
[1] TRUE
[1] TRUE
> 
> 
> proc.time()
   user  system elapsed 
   0.26    0.04    0.25