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skip_if_not_installed("mgcv")
set.seed(123)
void <- capture.output({
dat <- mgcv::gamSim(6, n = 200, scale = 0.2, dist = "poisson")
})
m1_gamm <- mgcv::gamm(
y ~ s(x0) + s(x1) + s(x2),
family = poisson,
data = dat,
random = list(fac = ~1),
verbosePQL = FALSE
)
test_that("ci", {
expect_equal(
ci(m1_gamm)$CI_low,
c(2.361598, NA, NA, NA),
tolerance = 1e-3
)
})
test_that("se", {
expect_equal(
standard_error(m1_gamm)$SE,
c(0.3476989, NA, NA, NA),
tolerance = 1e-3
)
})
test_that("p_value", {
expect_equal(
p_value(m1_gamm)$p,
c(0, 0, 0, 0),
tolerance = 1e-3
)
})
mp <- model_parameters(m1_gamm)
test_that("model_parameters", {
expect_equal(
mp$Coefficient,
c(3.0476, NA, NA, NA),
tolerance = 1e-3
)
})
test_that("model_parameters", {
expect_equal(
mp$df,
c(NA, 3.84696, 3.17389, 8.51855),
tolerance = 1e-3
)
})
test_that("model_parameters", {
expect_equal(
mp$df_error,
c(183.4606, NA, NA, NA),
tolerance = 1e-3
)
})
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