context('generalized double Pareto distribution')
set.seed(1234) # can comment out for non-automated tests
params <- data.frame(
alpha=c(1.5,2,2.5), xi=c(0.1, 1, 10))
integral.tol <- 1e-4
for (i in 1:nrow(params)) {
alpha = params$alpha[i]
xi = params$xi[i]
test_that(sprintf('GDP density integrates to 1 (alpha=%f, xi=%f)', alpha, xi), {
igral <- integrate(function(x) dgdp(x, alpha = alpha, xi = xi), lower=-Inf, upper=Inf)
expect_lt(abs(1 - igral$value), integral.tol)
})
limits <- c(0.5, 1.5, 50, 100)
lapply(limits, function(lim) {
msg <- sprintf('GDP density integrates to cdf (alpha=%f, xi=%f, 0 to %f)', alpha, xi, lim)
test_that(msg, {
igral <- integrate(function(x) dgdp(x, alpha = alpha, xi = xi), lower=-Inf, upper=lim)
p <- pgdp(lim, alpha = alpha, xi = xi)
expect_lt(abs(igral$value - p), integral.tol)
})
})
test_that(sprintf('KS test for GDP & cdf (alpha=%f, xi=%f)', alpha, xi), {
draws <- rgdp(1e5, alpha = alpha, xi = xi)
kt <- ks.test(draws, 'pgdp', alpha = alpha, xi = xi)
expect_gt(kt$p.value, 0.01)
})
test_that(sprintf('GDP cdf and inv cdf agree (alpha=%f, xi=%f)', alpha, xi), {
ps <- seq(0, 1, length.out = 5)
qs <- qgdp(ps, alpha = 1, xi = 1)
expect_equal(ps, pgdp(qs, alpha = 1, xi = 1))
})
}
test_that('GDP draws the right number of variates', {
ws <- rgdp(n = 243, alpha = 1.3, xi = 0.01)
expect_equal(243, length(ws))
})
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