R Under development (unstable) (2017-11-17 r73742) -- "Unsuffered Consequences" Copyright (C) 2017 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: 1.424 0.02 1.448 0 0 > >