tests/testthat/test-id_dc.R

In alexanderlange53/SVAR_Identification_Package: Data-Driven Identification of SVAR Models

# 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")
# })
#