nzp.Rout.save
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Version 2.0.1 (2004-11-15), ISBN 3-900051-07-0
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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)
+ cat("chi squared statistic =", chisqstat, "\n")
+ cat("degrees of freedom =", length(ecc) - 1, "\n")
+ cat("p-value =", pchisq(chisqstat, length(ecc) - 1, lower.tail = FALSE),
+ "\n")
+ foo <- rbind(cc, ecc)
+ dimnames(foo) <- list(c("observed", "expected"), as.character(xx))
+ print(foo)
+ }
>
> set.seed(42)
> nsim <- 1e4
>
> mu <- 2.0
> x <- rnzp(nsim, mu)
> do.chisq.test(x, mu, 8)
chi squared statistic = 2.593699
degrees of freedom = 7
p-value = 0.9198777
1 2 3 4 5 6 7
observed 3088.000 3130.000 2119.000 1056.000 408.0000 137.0000 43.00000
expected 3130.353 3130.353 2086.902 1043.451 417.3804 139.1268 39.75051
8
observed 16.00000
expected 12.68375
>
> mu <- 1.0
> x <- rnzp(nsim, mu)
> do.chisq.test(x, mu, 5)
chi squared statistic = 1.508611
degrees of freedom = 4
p-value = 0.825115
1 2 3 4 5
observed 5851.000 2872.000 970.0000 245.0000 51.00000
expected 5819.767 2909.884 969.9612 242.4903 57.89792
>
> mu <- 0.5
> x <- rnzp(nsim, mu)
> do.chisq.test(x, mu, 4)
chi squared statistic = 1.828864
degrees of freedom = 3
p-value = 0.6086739
1 2 3 4
observed 7661.00 1961.000 321.0000 51.00000
expected 7707.47 1926.868 321.1446 44.51738
>
> nsim <- 1e6
> mu <- 0.05
> x <- rnzp(nsim, mu)
> do.chisq.test(x, mu, 4)
chi squared statistic = 1.158501
degrees of freedom = 3
p-value = 0.7629738
1 2 3 4
observed 975182.0 24418.00 397.0000 3.000000
expected 975208.3 24380.21 406.3368 5.130428
>
> # 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
>
>
>