context("check accuracy of flex.test poisson")
set.seed(16)
data(nydf)
data(nyw)
coords <- cbind(nydf$longitude, nydf$latitude)
cases <- floor(nydf$cases)
pop <- nydf$population
outp <- flex.test(
coords = coords, cases = cases, pop = pop,
w = nyw, k = 10, nsim = 99, alpha = 1
)
invisible(capture.output(outp_ <- flex_test(
coords = coords, cases = cases, pop = pop,
w = nyw, k = 10, nsim = 99, alpha = 1
)))
# results taken from flex_test_ny_poisson_10nn_cartesian
test_that("check accuracy for flex.test poisson", {
expect_equal(
sort(outp$clusters[[1]]$locids),
c(85, 86, 88, 89, 90, 92, 93)
)
expect_equal(round(outp$clusters[[1]]$max_dist, 6), 0.245662)
expect_equal(outp$clusters[[1]]$cases, 39)
expect_equal(round(outp$clusters[[1]]$exp, 4), 16.3981)
expect_equal(round(outp$clusters[[1]]$smr, 5), 2.37832)
expect_equal(round(outp$clusters[[1]]$test_statistic, 4), 11.6713)
# p-values are tough to test, make sure results don't change
# in future versions since these were manually checked
expect_equal(outp$clusters[[1]]$pvalue, 0.01)
expect_equal(
sort(outp$clusters[[2]]$locids),
c(1, 2, 13, 15, 47, 49, 51)
)
expect_equal(round(outp$clusters[[2]]$max_dist, 7), 0.0507453)
expect_equal(outp$clusters[[2]]$cases, 31)
expect_equal(round(outp$clusters[[2]]$exp, 4), 13.4462)
expect_equal(round(outp$clusters[[2]]$smr, 5), 2.30548)
expect_equal(round(outp$clusters[[2]]$test_statistic, 5), 8.62939)
# p-values are tough to test, make sure results don't change
# in future versions since these were manually checked
expect_equal(outp$clusters[[2]]$pvalue, 0.05)
expect_equal(
sort(outp$clusters[[9]]$locids),
c(102, 103, 106)
)
expect_equal(round(outp$clusters[[9]]$max_dist, 6), 0.194769)
expect_equal(outp$clusters[[9]]$cases, 11)
expect_equal(round(outp$clusters[[9]]$exp, 5), 4.76234)
expect_equal(round(outp$clusters[[9]]$smr, 5), 2.30979)
expect_equal(round(outp$clusters[[9]]$test_statistic, 5), 3.00674)
# p-values are tough to test, make sure results don't change
# in future versions since these were manually checked
expect_equal(outp$clusters[[9]]$pvalue, 1)
})
# results taken from flex_test_ny_poisson_10nn_cartesian
test_that("check accuracy for flex_test poisson", {
expect_equal(
sort(outp_$clusters[[1]]$locids),
c(85, 86, 88, 89, 90, 92, 93)
)
expect_equal(round(outp_$clusters[[1]]$max_dist, 6), 0.245662)
expect_equal(outp_$clusters[[1]]$cases, 39)
expect_equal(round(outp_$clusters[[1]]$exp, 4), 16.3981)
expect_equal(round(outp_$clusters[[1]]$smr, 5), 2.37832)
expect_equal(round(outp_$clusters[[1]]$test_statistic, 4), 11.6713)
# p-values are tough to test, make sure results don't change
# in future versions since these were manually checked
expect_equal(outp_$clusters[[1]]$pvalue, 0.02)
expect_equal(
sort(outp_$clusters[[2]]$locids),
c(1, 2, 13, 15, 47, 49, 51)
)
expect_equal(round(outp_$clusters[[2]]$max_dist, 7), 0.0507453)
expect_equal(outp_$clusters[[2]]$cases, 31)
expect_equal(round(outp_$clusters[[2]]$exp, 4), 13.4462)
expect_equal(round(outp_$clusters[[2]]$smr, 5), 2.30548)
expect_equal(round(outp_$clusters[[2]]$test_statistic, 5), 8.62939)
# p-values are tough to test, make sure results don't change
# in future versions since these were manually checked
expect_equal(outp_$clusters[[2]]$pvalue, 0.09)
expect_equal(
sort(outp_$clusters[[9]]$locids),
c(102, 103, 106)
)
expect_equal(round(outp_$clusters[[9]]$max_dist, 6), 0.194769)
expect_equal(outp_$clusters[[9]]$cases, 11)
expect_equal(round(outp_$clusters[[9]]$exp, 5), 4.76234)
expect_equal(round(outp_$clusters[[9]]$smr, 5), 2.30979)
expect_equal(round(outp_$clusters[[9]]$test_statistic, 5), 3.00674)
# p-values are tough to test, make sure results don't change
# in future versions since these were manually checked
expect_equal(outp_$clusters[[9]]$pvalue, 1)
})
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