context("check accuracy of rflex.test binomial")
set.seed(15)
data(nydf)
data(nyw)
outb <- rflex.test(
coords = cbind(nydf$longitude, nydf$latitude),
cases = floor(nydf$cases),
pop = nydf$population,
w = nyw, k = 50,
nsim = 99, alpha = 1, longlat = FALSE,
alpha1 = 0.2,
type = "binomial"
)
# results taken from rflex_test_ny_binomial_50nn_cartesian
test_that("check accuracy for rflex.test binomial ", {
expect_equal(
sort(outb$clusters[[1]]$locids),
c(1:2, 13, 15, 27, 35, 37:38, 43, 46:47, 49, 51:53)
)
expect_equal(round(outb$clusters[[1]]$max_dist, 5), 0.22483)
expect_equal(outb$clusters[[1]]$cases, 79)
expect_equal(round(outb$clusters[[1]]$exp, 4), 36.1025)
expect_equal(round(outb$clusters[[1]]$smr, 5), 2.18822)
expect_equal(round(outb$clusters[[1]]$loglik, 4), 20.8156)
# p-values are tough to test, make sure results don't change
# in future versions since these were manually checked
expect_equal(outb$clusters[[1]]$pvalue, 0.01)
expect_equal(sort(outb$clusters[[2]]$locids), c(89, 90))
expect_equal(round(outb$clusters[[2]]$max_dist, 6), 0.125172)
expect_equal(outb$clusters[[2]]$cases, 13)
expect_equal(round(outb$clusters[[2]]$exp, 5), 3.46124)
expect_equal(round(outb$clusters[[2]]$smr, 5), 3.75588)
expect_equal(round(outb$clusters[[2]]$loglik, 5), 7.75475)
# p-values are tough to test, make sure results don't change
# in future versions since these were manually checked
expect_equal(round(outb$clusters[[2]]$pvalue, 1), 0.3)
expect_equal(
sort(outb$clusters[[12]]$locids),
c(135, 146, 208, 210)
)
expect_equal(round(outb$clusters[[12]]$max_dist, 6), 0.030934)
expect_equal(outb$clusters[[12]]$cases, 12)
expect_equal(round(outb$clusters[[12]]$exp, 5), 5.59582)
expect_equal(round(outb$clusters[[12]]$smr, 5), 2.14446)
expect_equal(round(outb$clusters[[12]]$loglik, 5), 2.79008)
# p-values are tough to test, make sure results don't change
# in future versions since these were manually checked
expect_equal(outb$clusters[[12]]$pvalue, 1)
})
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