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# Copyright (C) 2012 Yohan Chalabi
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License as
# published by the Free Software Foundation; either version 2 or 3 of
# the License (at your option).
#
# This program is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# General Public License for more details.
#
# A copy of the GNU General Public License is available at
# http://www.r-project.org/Licenses/
test.dgl <- function() {
# since dgl is based on pgl and qdgl and that these functions have
# been checked, we can simply implementation Rdgl with them:
Rdgl <- function(x, pars) {
p <- pgl(x, pars)
1/qdgl(p, pars)
}
tol <- 5 * .Machine$double.eps
###################################
# generate different sets of parameter values
iqr <- c(1, 2)
med <- c(-1, 0, 1)
chi <- c(-.75, -.5, -.25, 0, .25, .5, .75) # take care to include
xi <- unique(sort(.5 * (1. + c(chi, -chi)))) # special cases
params <- expand.grid(med, iqr, chi, xi)
params <- rbind(params,
c(0, 1, 0, .5 - 1/sqrt(5)), # special case
c(0, 1, 0, .5 - 2/sqrt(17)),
c(0, 1, 0, .5),
c(0, 1, 1, 0),
c(0, 1, -1, 0))
# special case with different location and scale
params <- rbind(params,
c(-1, 2, 0, .5 - 1/sqrt(5)),
c(-1, 2, 0, .5 - 2/sqrt(17)),
c(-1, 2, 0, .5),
c(-1, 2, 1, 0),
c(-1, 2, -1, 0))
params <- rbind(params,
c(1, 2, 0, .5 - 1/sqrt(5)),
c(1, 2, 0, .5 - 2/sqrt(17)),
c(1, 2, 0, .5),
c(1, 2, 1, 0),
c(1, 2, -1, 0))
###################################
# check if density integrates to one
for (i in seq.int(nrow(params))) {
pars <- as.numeric(params[i, ])
range <- qgl(c(0, 1), pars)
den <- integrate(dgl, range[1], range[2], med = pars,
subdivisions = 1e4)
checkTrue(den$value && (den$abs.error < 1e-3))
}
###################################
# check if we have the same result as with R implementation
for (i in seq.int(nrow(params))) {
pars <- as.numeric(params[i, ])
p <- seq(0, 1, len = 1e3)
x <- qgl(p, pars)
checkEquals(dgl(x, pars), Rdgl(x, pars))
}
###################################
# test included distribution
p <- seq(0, 1, len = 1e3)
# uniform
a <- 1; b <- 5
pars <- c(.5 * (a + b), .5 * (b - a), 0, .5 - 1/sqrt(5))
x <- qunif(p, min = a, max = b)
d <- dunif(x, min = a, max = b)
gd <- dgl(x, pars)
checkEquals(d, gd, tol)
pars <- c(.5 * (a + b), .5 * (b - a), 0, .5 - 2/sqrt(17))
gd <- dgl(x, pars)
checkEquals(d, gd, tol)
# logistic
loc <- 2; scale <- 3
q <- qlogis(p, loc, scale)
med <- loc; iqr <- scale * log(9); chi <- 0; xi <- .5
checkEquals(q, qgl(p, med, iqr, chi, xi), tol)
# exponential
rate <- 3
q <- qexp(p, rate)
med <- log(2)/rate; iqr <- log(3)/rate; chi <- 1; xi <- 0
checkEquals(q, qgl(p, med, iqr, chi, xi), tol)
med <- -log(2)/rate; iqr <- log(3)/rate; chi <- -1; xi <- 0
checkEquals(q, -qgl(1-p, med, iqr, chi, xi), tol)
###################################
# test with NaNs in vector
for (i in 1:nrow(params)) {
pars <- as.numeric(params[i, ])
p <- c(0, NaN, .25, NaN, .5, NaN, .75, NaN, 1, NaN)
x <- qgl(p, pars)
d <- dgl(x, pars)
# check if we really have NaNs back with pgl
checkIdentical(x[c(FALSE, TRUE)], rep(NaN, 5))
# and check that other values were not changed because of the
# NaNs
idx <- c(TRUE, FALSE)
checkEquals(dgl(x[idx], pars), d[idx], tol = tol)
}
###################################
# test with NaNs in vector
for (i in 1:nrow(params)) {
pars <- as.numeric(params[i, ])
p <- c(0, NA, .25, NA, .5, NA, .75, NA, 1, NA)
x <- qgl(p, pars)
d <- dgl(x, pars)
# check if we really have NAs back with pgl
checkIdentical(d[c(FALSE, TRUE)], rep(NA_real_, 5))
# and check that other values were not changed because of the
# NAs
idx <- c(TRUE, FALSE)
checkEquals(dgl(x[idx], pars), d[idx], tol = tol)
}
###################################
# test with values larger or smaller than distribution range
for (i in 1:nrow(params)) {
pars <- as.numeric(params[i, ])
xmin <- qgl(0, pars)
xmax <- qgl(1, pars)
if (is.finite(xmin)) {
x <- c(if (xmin < 0) xmin * 1.2 else xmin * .8, xmin)
d <- dgl(x, pars)
checkEquals(d, c(0, 1/qdgl(0, pars)), tol)
}
if (is.finite(xmax)) {
x <- c(xmax, if (xmax < 0) xmax * .8 else xmax * 1.2)
d <- dgl(x, pars)
checkEquals(d, c(1/qdgl(1, pars), 0), tol)
}
}
###################################
# test invalid options that should produce NaNs and warnings
oo <- options(warn = -1)
on.exit(options(oo))
checkTrue(all(is.nan(dgl(c(0, 0, 0), iqr = 0))))
checkTrue(all(is.nan(dgl(c(0, 0, 0), iqr = -1))))
checkTrue(all(is.nan(dgl(c(0, 0, 0), chi = -1))))
checkTrue(all(is.nan(dgl(c(0, 0, 0), chi = 1))))
checkTrue(all(is.nan(dgl(c(0, 0, 0), chi = 2))))
checkTrue(all(is.nan(dgl(c(0, 0, 0), chi = -2))))
checkTrue(all(is.nan(dgl(c(0, 0, 0), xi = 0))))
checkTrue(all(is.nan(dgl(c(0, 0, 0), xi = 1))))
checkTrue(all(is.nan(dgl(c(0, 0, 0), xi = -1))))
checkTrue(all(is.nan(dgl(c(0, 0, 0), xi = 2))))
options(warn = 2)
checkException(dgl(c(0, 0, 0), iqr = 0), silent = TRUE)
checkException(dgl(c(0, 0, 0), iqr = -1), silent = TRUE)
checkException(dgl(c(0, 0, 0), chi = -1), silent = TRUE)
checkException(dgl(c(0, 0, 0), chi = 1), silent = TRUE)
checkException(dgl(c(0, 0, 0), chi = 2), silent = TRUE)
checkException(dgl(c(0, 0, 0), chi = -2), silent = TRUE)
checkException(dgl(c(0, 0, 0), xi = 0), silent = TRUE)
checkException(dgl(c(0, 0, 0), xi = 1), silent = TRUE)
checkException(dgl(c(0, 0, 0), xi = -1), silent = TRUE)
checkException(dgl(c(0, 0, 0), xi = 2), silent = TRUE)
options(oo)
}
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