# context("test-id_dc.R")
#
# test_that("id.dc 3-dims PIT = FALSE works", {
# skip_on_cran()
# set.seed(23211)
# v1 <- vars::VAR(USA, lag.max = 10, ic = "AIC" )
# x1 <- id.dc(v1)
#
# expect_equal(sum(round(x1$B, 4)), 2.8498)
#
# expect_equal(x1$K, 3)
# expect_equal(x1$n, 169)
# expect_equal(x1$PIT, FALSE)
# expect_equal(x1$p, 6)
#
# expect_match(x1$method, "Distance covariances")
# })
#
# test_that("id.dc 3-dims PIT = TRUE works", {
# skip_on_cran()
# set.seed(23211)
# v1 <- vars::VAR(USA, lag.max = 10, ic = "AIC" )
# x1 <- id.dc(v1, PIT = TRUE)
#
# expect_equal(sum(round(x1$B, 4)), 2.5394)
#
# expect_equal(x1$K, 3)
# expect_equal(x1$n, 169)
# expect_equal(x1$PIT, TRUE)
# expect_equal(x1$p, 6)
#
# expect_match(x1$method, "Distance covariances")
# })
#
# test_that("id.dc 3-dims PIT = TRUE works", {
# skip_on_cran()
# set.seed(23211)
# v1 <- vars::VAR(USA, lag.max = 10, ic = "AIC" )
# x1 <- id.dc(v1, PIT = TRUE)
#
# expect_equal(sum(round(x1$B, 4)), 2.5394)
#
# expect_equal(x1$K, 3)
# expect_equal(x1$n, 169)
# expect_equal(x1$PIT, TRUE)
# expect_equal(x1$p, 6)
#
# expect_match(x1$method, "Distance covariances")
# })
#
# test_that("id.dc 2-dims PIT = FALSE works", {
# skip_on_cran()
# set.seed(23211)
# v1 <- vars::VAR(USA[,-3], p = 3, ic = "AIC" )
# x1 <- id.dc(v1)
#
# expect_equal(sum(round(x1$B, 4)), 1.8296)
#
# expect_equal(x1$K, 2)
# expect_equal(x1$n, 172)
# expect_equal(x1$PIT, FALSE)
# expect_equal(x1$p, 3)
#
# expect_match(x1$method, "Distance covariances")
# })
#
# test_that("id.dc 2-dims PIT = FALSE works with trend + constant", {
# skip_on_cran()
# set.seed(23211)
# v1 <- vars::VAR(USA[,-3], p = 3, type = 'both' )
# x1 <- id.dc(v1)
#
# expect_equal(sum(round(x1$B, 4)), 1.8102)
#
# expect_equal(x1$K, 2)
# expect_equal(x1$n, 172)
# expect_equal(x1$PIT, FALSE)
# expect_equal(x1$p, 3)
#
# expect_match(x1$method, "Distance covariances")
# })
#
# test_that("id.dc 2-dims PIT = FALSE works without deterministic term", {
# skip_on_cran()
# set.seed(23211)
# v1 <- vars::VAR(USA[,-3], p = 3, type = 'none' )
# x1 <- id.dc(v1)
#
# expect_equal(sum(round(x1$B, 4)), 1.8441)
#
# expect_equal(x1$K, 2)
# expect_equal(x1$n, 172)
# expect_equal(x1$PIT, FALSE)
# expect_equal(x1$p, 3)
#
# expect_match(x1$method, "Distance covariances")
# })
#
# test_that("id.dc 2-dims PIT = TRUE works", {
# skip_on_cran()
# set.seed(23211)
# v1 <- vars::VAR(USA[,-3], p = 3, ic = "AIC" )
# x1 <- id.dc(v1, PIT = TRUE)
#
# expect_equal(sum(round(x1$B, 4)), 1.8734)
#
# expect_equal(x1$K, 2)
# expect_equal(x1$n, 172)
# expect_equal(x1$PIT, TRUE)
# expect_equal(x1$p, 3)
#
# expect_match(x1$method, "Distance covariances")
# })
#
# test_that("restricted id.dc 3-dims PIT = FALSE works with restricted var and constant", {
# skip_on_cran()
# set.seed(23211)
# v1 <- vars::VAR(USA, p = 3, type = "const")
# # Form vars example
# restrict <- matrix(c(1, 1, 1, 1, 1, 1, 0, 0, 0,1,
# 1, 0, 1, 0, 0, 1, 0, 1, 1,1,
# 0, 0, 1, 1, 0, 1, 0, 0, 1,1),
# nrow=3, ncol=10, byrow=TRUE)
# vRes = restrict(v1, method = "man", resmat = restrict)
#
# x1 <- id.dc(vRes)
#
# expect_equal(sum(round(x1$B, 4)), 3.4498)
#
# expect_equal(x1$K, 3)
# expect_equal(x1$n, 172)
# expect_equal(x1$PIT, FALSE)
# expect_equal(x1$p, 3)
#
# expect_match(x1$method, "Distance covariances")
# })
#
# test_that("id.dc 3-dims PIT = FALSE works with restricted var and trend", {
# skip_on_cran()
# set.seed(23211)
# v1 <- vars::VAR(USA, p = 3, type = "trend")
# # Form vars example
# restrict <- matrix(c(1, 1, 1, 1, 1, 1, 0, 0, 0,1,
# 1, 0, 1, 0, 0, 1, 0, 1, 1,1,
# 0, 0, 1, 1, 0, 1, 0, 0, 1,1),
# nrow=3, ncol=10, byrow=TRUE)
# vRes = restrict(v1, method = "man", resmat = restrict)
#
# x1 <- id.dc(vRes)
#
# expect_equal(sum(round(x1$B, 4)), 3.6068)
#
# expect_equal(x1$K, 3)
# expect_equal(x1$n, 172)
# expect_equal(x1$PIT, FALSE)
# expect_equal(x1$p, 3)
#
# expect_match(x1$method, "Distance covariances")
# })
#
#
# test_that("id.dc 3-dims PIT = FALSE works with restricted var and constant + trend", {
# skip_on_cran()
#
# set.seed(23211)
# v1 <- vars::VAR(USA, p = 3, type = "both")
# # Form vars example
# restrict <- matrix(c(1, 1, 1, 1, 1, 1, 0, 0, 0,1,1,
# 1, 0, 1, 0, 0, 1, 0, 1, 1,1,1,
# 0, 0, 1, 1, 0, 1, 0, 0, 1,1,1),
# nrow=3, ncol=11, byrow=TRUE)
# vRes = restrict(v1, method = "man", resmat = restrict)
#
# x1 <- id.dc(vRes)
#
# expect_equal(sum(round(x1$B, 4)), 2.643)
#
# expect_equal(x1$K, 3)
# expect_equal(x1$n, 172)
# expect_equal(x1$PIT, FALSE)
# expect_equal(x1$p, 3)
#
# expect_match(x1$method, "Distance covariances")
# })
#
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