Nothing
skip_on_travis()
skip_on_cran()
SEED <- 1001
set.seed(SEED)
data("colon")
dat <- split_data(colon$X, colon$y, p.train = 0.9)
set.seed(SEED)
mlr <- gendata_MLR(n = 50, p = 10)
dat3 <- split_data(mlr$X, mlr$y, p.train = 0.8)
expect_equal_predict <- function(actual, expected) {
expect_equal(unname(actual$probs_pred), unname(expected$probs_pred))
}
expect_equal_htlr <- function(actual, expected)
{
expect_equal(actual$mcdeltas, expected$mcdeltas)
expect_equal(as.vector(actual$mclogw), expected$mclogw)
expect_equal(as.vector(actual$mcloglike), expected$mcloglike)
expect_equal(as.vector(actual$mcuvar), expected$mcuvar)
expect_equal(as.vector(actual$mchmcrej), expected$mchmcrej)
expect_equal(actual$mcsigmasbt, expected$mcsigmasbt)
expect_equal(actual$mcvardeltas, expected$mcvardeltas)
expect_equal_predict(actual, expected)
}
test_that("colon500_t1_s10_eta10_bcbc_bi", {
set.seed(SEED)
fit <- htlr_fit(X_tr = dat$x.tr, y_tr = dat$y.tr, X_ts = dat$x.te,
fsel = 1L:500, ptype = "t", alpha = 1, s = -10, eta = 10,
initial_state = "bcbcsfrda", iters_h = 5, iters_rmc = 5, thin = 1)
set.seed(SEED)
expected <- HTLR.old::htlr_fit(X_tr = dat$x.tr, y_tr = dat$y.tr, X_ts = dat$x.te,
fsel = 1L:500, ptype = "t", alpha = 1, s = -10, eta = 10,
initial_state = "bcbcsfrda", iters_h = 5, iters_rmc = 5, thin = 1)
expect_equal_htlr(fit, expected)
})
test_that("sim_t1_s10_eta10_bcbc_mul", {
set.seed(SEED)
fit <- htlr_fit(X_tr = dat3$x.tr, y_tr = dat3$y.tr, X_ts = dat3$x.te,
ptype = "t", alpha = 1, s = -10, eta = 10,
initial_state = "bcbcsfrda", iters_h = 5, iters_rmc = 5, thin = 1)
set.seed(SEED)
expected <- HTLR.old::htlr_fit(X_tr = dat3$x.tr, y_tr = dat3$y.tr, X_ts = dat3$x.te,
ptype = "t", alpha = 1, s = -10, eta = 10,
initial_state = "bcbcsfrda", iters_h = 5, iters_rmc = 5, thin = 1)
expect_equal_htlr(fit, expected)
})
test_that("colon500_neg1_s10_eta0_bcbc_bi", {
set.seed(SEED)
fit <- htlr_fit(X_tr = dat$x.tr, y_tr = dat$y.tr, X_ts = dat$x.te,
fsel = 1L:500, ptype = "neg", alpha = 1, s = -10,
initial_state = "bcbcsfrda", iters_h = 5, iters_rmc = 5, thin = 1)
set.seed(SEED)
expected <- HTLR.old::htlr_fit(X_tr = dat$x.tr, y_tr = dat$y.tr, X_ts = dat$x.te,
fsel = 1L:500, ptype = "neg", alpha = 1, s = -10,
initial_state = "bcbcsfrda", iters_h = 5, iters_rmc = 5, thin = 1)
expect_equal_htlr(fit, expected)
})
test_that("colon500_ghs1_s10_eta0_bcbc_bi", {
set.seed(SEED)
fit <- htlr_fit(X_tr = dat$x.tr, y_tr = dat$y.tr, X_ts = dat$x.te,
fsel = 1L:500, ptype = "ghs", alpha = 1, s = -10,
initial_state = "bcbcsfrda", iters_h = 5, iters_rmc = 5, thin = 1)
set.seed(SEED)
expected <- HTLR.old::htlr_fit(X_tr = dat$x.tr, y_tr = dat$y.tr, X_ts = dat$x.te,
fsel = 1L:500, ptype = "ghs", alpha = 1, s = -10,
initial_state = "bcbcsfrda", iters_h = 5, iters_rmc = 5, thin = 1)
expect_equal_htlr(fit, expected)
})
# test_that("colon500_t1_s10_eta10_lasso_bi", {
# set.seed(SEED)
# fit <- htlr_fit(X_tr = dat$x.tr, y_tr = dat$y.tr, X_ts = dat$x.te,
# fsel = 1L:500, ptype = "t", alpha = 1, s = -10, eta = 10,
# initial_state = "lasso", iters_h = 0, iters_rmc = 1, thin = 1)
#
# set.seed(SEED)
# expected <- HTLR.old::htlr_fit(X_tr = dat$x.tr, y_tr = dat$y.tr, X_ts = dat$x.te,
# fsel = 1L:500, ptype = "t", alpha = 1, s = -10, eta = 10,
# initial_state = "lasso", iters_h = 0, iters_rmc = 1, thin = 1)
# expect_equal_htlr(fit, expected)
# })
# HoSC <- list("x.train" = read.csv("../../data-raw/HoCS_train_data.csv", header = F),
# "x.test" = read.csv("../../data-raw/HoCS_test_data.csv", header = F),
# "y.train" = rep(1:3, each = 10),
# "y.test" = c(rep(1, 50), rep(2, 27), rep(3, 52)))
#
# test_that("data_with_singular_col", {
# fit.1 <- htlr(X = HoSC$x.train, y = HoSC$y.train, init = "bcbc", iter = 10)
# fit.2 <- htlr_fit(X_tr = HoSC$x.train, y_tr = HoSC$y.train, ptype = "t",
# initial_state = "lasso", iters_h = 5, iters_rmc = 5, thin = 1)
#
# expect_equal(length(fit.1$featur$fsel), 86)
# expect_equal(length(fit.2$featur$fsel), 86)
#
# pred <- predict(fit.1, HoSC$x.test)
# })
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