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) })