Nothing
skip_on_cran()
skip_if_not_installed("mgcv")
test_that("finds_*", {
set.seed(123)
n <- 500
xn <- rep(c(1, 2, 3), n)
levels <- sort(unique(xn))
labels <- c("low", "med", "high")
x <- factor(xn, levels = levels, labels = labels)
z <- sample(c(1, 2, 3, 3, 4, 4, 5, 5, 6, 7, 7, 7, 7), size = length(x), replace = TRUE)
y.raw <- xn * z
e <- rnorm(length(x), sd = sd(y.raw))
y <- y.raw + e
data <- data.frame(x, y, z)
w <- 3
m1 <- mgcv::gam(y ~ s(z, by = x, k = 3) + x, data = data)
m2 <- mgcv::gam(y ~ s(z, by = x, k = w) + x, data = data)
# find_predictors()
expect_identical(find_predictors(m1), find_predictors(m2))
expect_identical(find_predictors(m2)$conditional, c("z", "x"))
# find_variables()
expect_identical(find_variables(m1), find_variables(m2))
expect_identical(find_variables(m2)$conditional, c("z", "x"))
# find_terms()
expect_identical(
find_terms(m1),
list(response = "y", conditional = c("s(z, by = x, k = 3)", "x"))
)
expect_identical(
find_terms(m2),
list(response = "y", conditional = c("s(z, by = x, k = w)", "x"))
)
# get_predictors()
out <- head(get_predictors(m1))
expect_named(out, c("z", "x"))
})
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