test_that("insight::get_predicted", {
skip_on_os("mac")
skip_if_not_or_load_if_installed("rstanarm")
x <- suppressWarnings(
insight::get_predicted(
stan_glm(hp ~ mpg, data = mtcars, iter = 500, refresh = 0)
)
)
rez <- point_estimate(x, use_iterations = TRUE)
expect_identical(c(nrow(rez), ncol(rez)), c(32L, 4L))
rez <- point_estimate(x, use_iterations = FALSE)
expect_identical(c(nrow(rez), ncol(rez)), c(1L, 3L))
rez <- hdi(x, use_iterations = TRUE)
expect_identical(c(nrow(rez), ncol(rez)), c(32L, 4L))
rez <- hdi(x, use_iterations = FALSE)
expect_identical(c(nrow(rez), ncol(rez)), c(1L, 3L))
rez <- eti(x, use_iterations = TRUE)
expect_identical(c(nrow(rez), ncol(rez)), c(32L, 4L))
rez <- eti(x, use_iterations = FALSE)
expect_identical(c(nrow(rez), ncol(rez)), c(1L, 3L))
rez <- ci(x, use_iterations = TRUE)
expect_identical(c(nrow(rez), ncol(rez)), c(32L, 4L))
rez <- ci(x, use_iterations = FALSE)
expect_identical(c(nrow(rez), ncol(rez)), c(1L, 3L))
rez <- map_estimate(x, use_iterations = TRUE)
expect_identical(c(nrow(rez), ncol(rez)), c(32L, 2L))
rez <- map_estimate(x, use_iterations = FALSE)
expect_identical(c(nrow(rez), ncol(rez)), c(1L, 2L))
rez <- p_direction(x, use_iterations = TRUE)
expect_identical(c(nrow(rez), ncol(rez)), c(32L, 2L))
rez <- p_direction(x, use_iterations = FALSE)
expect_identical(c(nrow(rez), ncol(rez)), c(1L, 2L))
rez <- p_map(x, use_iterations = TRUE)
expect_identical(c(nrow(rez), ncol(rez)), c(32L, 2L))
rez <- p_map(x, use_iterations = FALSE)
expect_identical(c(nrow(rez), ncol(rez)), c(1L, 2L))
rez <- p_significance(x, use_iterations = TRUE)
expect_identical(c(nrow(rez), ncol(rez)), c(32L, 2L))
rez <- p_significance(x, use_iterations = FALSE)
expect_identical(c(nrow(rez), ncol(rez)), c(1L, 2L))
rez <- rope(x, use_iterations = TRUE)
expect_identical(c(nrow(rez), ncol(rez)), c(32L, 5L))
rez <- rope(x, use_iterations = FALSE)
expect_identical(c(nrow(rez), ncol(rez)), c(1L, 4L))
rez <- describe_posterior(x, use_iterations = TRUE)
expect_identical(c(nrow(rez), ncol(rez)), c(32L, 5L))
rez <- estimate_density(x, use_iterations = TRUE)
expect_identical(c(nrow(rez), ncol(rez)), c(1024L, 2L))
})
test_that("bayesQR", {
skip_on_os("mac")
skip_if_not_or_load_if_installed("bayesQR")
invisible(capture.output({
x <- bayesQR(Sepal.Length ~ Petal.Width,
data = iris, quantile = 0.1,
alasso = TRUE, ndraw = 500
)
}))
rez <- p_direction(x)
expect_identical(c(nrow(rez), ncol(rez)), c(2L, 2L))
rez <- p_map(x)
expect_identical(c(nrow(rez), ncol(rez)), c(2L, 2L))
rez <- p_significance(x)
expect_identical(c(nrow(rez), ncol(rez)), c(2L, 2L))
rez <- rope(x)
expect_identical(c(nrow(rez), ncol(rez)), c(2L, 5L))
rez <- hdi(x)
expect_identical(c(nrow(rez), ncol(rez)), c(2L, 4L))
rez <- eti(x)
expect_identical(c(nrow(rez), ncol(rez)), c(2L, 4L))
rez <- map_estimate(x)
expect_identical(c(nrow(rez), ncol(rez)), c(2L, 2L))
rez <- point_estimate(x)
expect_identical(c(nrow(rez), ncol(rez)), c(2L, 4L))
rez <- describe_posterior(x)
expect_identical(c(nrow(rez), ncol(rez)), c(2L, 10L))
rez <- estimate_density(x)
expect_identical(c(nrow(rez), ncol(rez)), c(2048L, 3L))
})
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