R version 3.3.0 beta (2016-04-19 r70517) -- "Supposedly Educational"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> ##
> ## RNG tests using DKW inequality for rate of convergence
> ##
> ## P(sup | F_n - F | > t) < 2 exp(-2nt^2)
> ##
> ## The 2 in front of exp() was derived by Massart. It is the best possible
> ## constant valid uniformly in t,n,F. For large n*t^2 this agrees with the
> ## large-sample approximation to the Kolmogorov-Smirnov statistic.
> ##
> 
> 
> superror <- function(rfoo,pfoo,sample.size,...) {
+     x <- rfoo(sample.size,...)
+     tx <- table(signif(x, 12)) # such that xi will be sort(unique(x))
+     xi <- as.numeric(names(tx))
+     f <- pfoo(xi,...)
+     fhat <- cumsum(tx)/sample.size
+     max(abs(fhat-f))
+ }
> 
> pdkwbound <- function(n,t) 2*exp(-2*n*t*t)
> 
> qdkwbound <- function(n,p) sqrt(log(p/2)/(-2*n))
> 
> dkwtest <- function(stub = "norm", ...,
+                     sample.size = 10000, pthreshold = 0.001,
+                     print.result = TRUE, print.detail = FALSE,
+                     stop.on.failure = TRUE)
+ {
+     rfoo <- eval(as.name(paste("r", stub, sep="")))
+     pfoo <- eval(as.name(paste("p", stub, sep="")))
+     s <- superror(rfoo, pfoo, sample.size, ...)
+     if (print.result || print.detail) {
+         printargs <- substitute(list(...))
+         printargs[[1]] <- as.name(stub)
+         cat(deparse(printargs))
+         if (print.detail)
+             cat("\nsupremum error = ",signif(s,2),
+                 " with p-value=",min(1,round(pdkwbound(sample.size,s),4)),"\n")
+     }
+     rval <- (s < qdkwbound(sample.size,pthreshold))
+     if (print.result)
+         cat(c(" FAILED\n"," PASSED\n")[rval+1])
+     if (stop.on.failure && !rval)
+         stop("dkwtest failed")
+     rval
+ }
> 
> .proctime00 <- proc.time() # start timing
> 
> 
> dkwtest("binom",size =   1,prob = 0.2)
binom(size = 1, prob = 0.2) PASSED
[1] TRUE
> dkwtest("binom",size =   2,prob = 0.2)
binom(size = 2, prob = 0.2) PASSED
[1] TRUE
> dkwtest("binom",size = 100,prob = 0.2)
binom(size = 100, prob = 0.2) PASSED
[1] TRUE
> dkwtest("binom",size = 1e4,prob = 0.2)
binom(size = 10000, prob = 0.2) PASSED
[1] TRUE
> dkwtest("binom",size =   1,prob = 0.8)
binom(size = 1, prob = 0.8) PASSED
[1] TRUE
> dkwtest("binom",size = 100,prob = 0.8)
binom(size = 100, prob = 0.8) PASSED
[1] TRUE
> dkwtest("binom",size = 100,prob = 0.999)
binom(size = 100, prob = 0.999) PASSED
[1] TRUE
> 
> dkwtest("pois",lambda =  0.095)
pois(lambda = 0.095) PASSED
[1] TRUE
> dkwtest("pois",lambda =  0.95)
pois(lambda = 0.95) PASSED
[1] TRUE
> dkwtest("pois",lambda =  9.5)
pois(lambda = 9.5) PASSED
[1] TRUE
> dkwtest("pois",lambda = 95)
pois(lambda = 95) PASSED
[1] TRUE
> 
> dkwtest("nbinom",size =   1,prob = 0.2)
nbinom(size = 1, prob = 0.2) PASSED
[1] TRUE
> dkwtest("nbinom",size =   2,prob = 0.2)
nbinom(size = 2, prob = 0.2) PASSED
[1] TRUE
> dkwtest("nbinom",size = 100,prob = 0.2)
nbinom(size = 100, prob = 0.2) PASSED
[1] TRUE
> dkwtest("nbinom",size = 1e4,prob = 0.2)
nbinom(size = 10000, prob = 0.2) PASSED
[1] TRUE
> dkwtest("nbinom",size =   1,prob = 0.8)
nbinom(size = 1, prob = 0.8) PASSED
[1] TRUE
> dkwtest("nbinom",size = 100,prob = 0.8)
nbinom(size = 100, prob = 0.8) PASSED
[1] TRUE
> dkwtest("nbinom",size = 100,prob = 0.999)
nbinom(size = 100, prob = 0.999) PASSED
[1] TRUE
> 
> dkwtest("norm")
norm() PASSED
[1] TRUE
> dkwtest("norm",mean = 5,sd = 3)
norm(mean = 5, sd = 3) PASSED
[1] TRUE
> 
> dkwtest("gamma",shape =  0.1)
gamma(shape = 0.1) PASSED
[1] TRUE
> dkwtest("gamma",shape =  0.2)
gamma(shape = 0.2) PASSED
[1] TRUE
> dkwtest("gamma",shape = 10)
gamma(shape = 10) PASSED
[1] TRUE
> dkwtest("gamma",shape = 20)
gamma(shape = 20) PASSED
[1] TRUE
> 
> dkwtest("hyper",m = 40,n = 30,k = 20)
hyper(m = 40, n = 30, k = 20) PASSED
[1] TRUE
> dkwtest("hyper",m = 40,n =  3,k = 20)
hyper(m = 40, n = 3, k = 20) PASSED
[1] TRUE
> dkwtest("hyper",m =  6,n =  3,k =  2)
hyper(m = 6, n = 3, k = 2) PASSED
[1] TRUE
> dkwtest("hyper",m =  5,n =  3,k =  2)
hyper(m = 5, n = 3, k = 2) PASSED
[1] TRUE
> dkwtest("hyper",m =  4,n =  3,k =  2)
hyper(m = 4, n = 3, k = 2) PASSED
[1] TRUE
> 
> 
> dkwtest("signrank",n =  1)
signrank(n = 1) PASSED
[1] TRUE
> dkwtest("signrank",n =  2)
signrank(n = 2) PASSED
[1] TRUE
> dkwtest("signrank",n = 10)
signrank(n = 10) PASSED
[1] TRUE
> dkwtest("signrank",n = 30)
signrank(n = 30) PASSED
[1] TRUE
> 
> dkwtest("wilcox",m = 40,n = 30)
wilcox(m = 40, n = 30) PASSED
[1] TRUE
> dkwtest("wilcox",m = 40,n = 10)
wilcox(m = 40, n = 10) PASSED
[1] TRUE
> dkwtest("wilcox",m =  6,n =  3)
wilcox(m = 6, n = 3) PASSED
[1] TRUE
> dkwtest("wilcox",m =  5,n =  3)
wilcox(m = 5, n = 3) PASSED
[1] TRUE
> dkwtest("wilcox",m =  4,n =  3)
wilcox(m = 4, n = 3) PASSED
[1] TRUE
> 
> dkwtest("chisq",df =  1)
chisq(df = 1) PASSED
[1] TRUE
> dkwtest("chisq",df = 10)
chisq(df = 10) PASSED
[1] TRUE
> 
> dkwtest("logis")
logis() PASSED
[1] TRUE
> dkwtest("logis",location = 4,scale = 2)
logis(location = 4, scale = 2) PASSED
[1] TRUE
> 
> dkwtest("t",df =  1)
t(df = 1) PASSED
[1] TRUE
> dkwtest("t",df = 10)
t(df = 10) PASSED
[1] TRUE
> dkwtest("t",df = 40)
t(df = 40) PASSED
[1] TRUE
> 
> dkwtest("beta",shape1 = 1, shape2 = 1)
beta(shape1 = 1, shape2 = 1) PASSED
[1] TRUE
> dkwtest("beta",shape1 = 2, shape2 = 1)
beta(shape1 = 2, shape2 = 1) PASSED
[1] TRUE
> dkwtest("beta",shape1 = 1, shape2 = 2)
beta(shape1 = 1, shape2 = 2) PASSED
[1] TRUE
> dkwtest("beta",shape1 = 2, shape2 = 2)
beta(shape1 = 2, shape2 = 2) PASSED
[1] TRUE
> dkwtest("beta",shape1 = .2,shape2 = .2)
beta(shape1 = 0.2, shape2 = 0.2) PASSED
[1] TRUE
> 
> dkwtest("cauchy")
cauchy() PASSED
[1] TRUE
> dkwtest("cauchy",location = 4,scale = 2)
cauchy(location = 4, scale = 2) PASSED
[1] TRUE
> 
> dkwtest("f",df1 =  1,df2 =  1)
f(df1 = 1, df2 = 1) PASSED
[1] TRUE
> dkwtest("f",df1 =  1,df2 = 10)
f(df1 = 1, df2 = 10) PASSED
[1] TRUE
> dkwtest("f",df1 = 10,df2 = 10)
f(df1 = 10, df2 = 10) PASSED
[1] TRUE
> dkwtest("f",df1 = 30,df2 =  3)
f(df1 = 30, df2 = 3) PASSED
[1] TRUE
> 
> dkwtest("weibull",shape = 1)
weibull(shape = 1) PASSED
[1] TRUE
> dkwtest("weibull",shape = 4,scale = 4)
weibull(shape = 4, scale = 4) PASSED
[1] TRUE
> 
> ## regression test for PR#7314
> dkwtest("hyper", m=60, n=100, k=50)
hyper(m = 60, n = 100, k = 50) PASSED
[1] TRUE
> dkwtest("hyper", m=6, n=10, k=5)
hyper(m = 6, n = 10, k = 5) PASSED
[1] TRUE
> dkwtest("hyper", m=600, n=1000, k=500)
hyper(m = 600, n = 1000, k = 500) PASSED
[1] TRUE
> 
> ## regression test for non-central t bug
> dkwtest("t", df=20, ncp=3)
t(df = 20, ncp = 3) PASSED
[1] TRUE
> ## regression test for non-central F bug
> dkwtest("f", df1=10, df2=2, ncp=3)
f(df1 = 10, df2 = 2, ncp = 3) PASSED
[1] TRUE
> 
> 
> cat('Time elapsed: ', proc.time() - .proctime00,'\n')
Time elapsed:  1.233 0.004 1.237 0 0 
> 
>