skip_if_not_installed("performance")
test_that("describe_nonlinear", {
set.seed(123)
d <- data.frame(x = rnorm(200))
d$y <- d$x^2 + rnorm(200, 0, 0.5)
model <- lm(y ~ poly(x, 2), data = d)
link_data <- estimate_relation(model, length = 100)
out <- describe_nonlinear(link_data, x = "x")
expect_equal(out$Start, c(-2.309, -0.011), tolerance = 1e-4)
expect_equal(out$End, c(-0.011, 3.241), tolerance = 1e-4)
expect_error(describe_nonlinear(link_data), regex = "The name of the predictor")
expect_error(describe_nonlinear(link_data, x = "x", y = "test"), regex = "The name of the response")
})
# test_that("estimate_smooth", {
# skip_on_cran()
# skip_if_not_installed("rstanarm")
# set.seed(333)
#
# model <-
# suppressWarnings(
# rstanarm::stan_gamm4(
# Sepal.Width ~ s(Petal.Length),
# data = iris,
# refresh = 0,
# iter = 200,
# chains = 2,
# seed = 333
# )
# )
# estim <- estimate_smooth(model)
# expect_equal(ncol(estim), 6)
#
# model <-
# suppressWarnings(
# rstanarm::stan_glm(
# Sepal.Width ~ poly(Petal.Length, 2),
# data = iris,
# refresh = 0,
# iter = 200,
# chains = 2,
# seed = 333
# )
# )
# estim <- estimate_smooth(model)
# expect_equal(c(nrow(estim), ncol(estim)), c(2, 6))
#
# model <-
# suppressWarnings(
# rstanarm::stan_glm(
# Sepal.Width ~ Species * poly(Petal.Length, 2),
# data = iris,
# refresh = 0,
# iter = 200,
# chains = 2,
# seed = 333
# )
# )
# estim <- estimate_smooth(model)
# expect_equal(ncol(estim), 6)
# estim <- estimate_smooth(model, levels = "Species")
# expect_equal(ncol(estim), 7)
# })
#
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