context("boot")
skip_on_cran()
skip_if_not_installed("modeltests")
library(modeltests)
skip_if_not_installed("boot")
library(boot)
test_that("boot tidier arguments", {
check_arguments(tidy.boot)
})
test_that("tidy.boot for glms", {
clotting <- data.frame(
u = c(5, 10, 15, 20, 30, 40, 60, 80, 100),
lot1 = c(118, 58, 42, 35, 27, 25, 21, 19, 18),
lot2 = c(69, 35, 26, 21, 18, 16, 13, 12, 12)
)
g1 <- glm(lot2 ~ log(u), data = clotting, family = Gamma)
boot_fun <- function(d, i) {
stats::coef(stats::update(g1, data = d[i, ]))
}
bootres <- boot::boot(clotting, boot_fun, R = 100)
td <- tidy(bootres, conf.int = TRUE)
tdnorm <- tidy(bootres, conf.int = TRUE, conf.method = "norm")
expect_false(any(is.na(tdnorm[[4]])))
bootresw <- boot::boot(clotting, boot_fun, R = 100, weights = rep(1 / 9, 9))
tdw <- tidy(bootresw, conf.int = TRUE)
tdwe <- tidy(bootresw, conf.int = TRUE, exponentiate = TRUE)
check_tidy_output(td)
check_tidy_output(tdw)
check_tidy_output(tdwe)
check_dims(td, 2, 6)
check_dims(tdw, 2, 7)
check_dims(tdwe, 2, 7)
expect_equal(exp(tdw$statistic), tdwe$statistic)
expect_equal(exp(tdw$conf.low), tdwe$conf.low)
})
test_that("tidy.boot for time series", {
lynx.fun <- function(tsb) {
ar.fit <- ar(tsb, order.max = 25)
c(ar.fit$order, mean(tsb), tsb)
}
lynx <- boot::tsboot(log(lynx), lynx.fun, R = 99, l = 20, orig.t = FALSE)
td <- tidy(lynx)
check_tidy_output(td)
check_dims(td, expected_cols = 2)
})
Generated by dwww version 1.15 on Sat May 18 09:43:55 CEST 2024.