Nothing
# context("id.st")
#
# test_that("unrestricted id.st estimation with pre specified c and gamma works 3-dim works", {
# skip_on_cran()
# set.seed(23211)
# v1 <- vars::VAR(USA, p = 6, ic = "AIC")
# x1 <- id.st(v1, c_fix = 80, gamma_fix = -1)
#
# expect_equal(round(x1$Lik, 4), -516.8098)
# expect_equal(round(sum(diag(x1$Lambda)),4), 0.633)
# expect_equal(round(sum(x1$B),4), 3.5697)
#
# expect_equal(round(sum(x1$Lambda_SE), 4), 0.1393)
#
# expect_equal(x1$K, 3)
# expect_equal(x1$n,169)
# expect_equal(x1$restrictions,0)
# expect_equal(x1$est_c, 80)
# expect_equal(x1$p, 6)
# expect_equal(x1$iteration, 5)
#
# expect_match(x1$method, "Smooth transition")
#
# })
#
# test_that("unrestricted id.st estimation with pre specified c and gamma works 3-dim works with constant + trend", {
# skip_on_cran()
# set.seed(23211)
# v1 <- vars::VAR(USA, p = 6, ic = "AIC", type = 'both')
# x1 <- id.st(v1, c_fix = 80, gamma_fix = -1)
#
# expect_equal(round(x1$Lik, 4), -510.3289)
# expect_equal(round(sum(diag(x1$Lambda)),4), 0.6418)
# expect_equal(round(sum(x1$B),4), 3.5395)
#
# expect_equal(round(sum(x1$Lambda_SE), 4), 0.1409)
#
# expect_equal(x1$K, 3)
# expect_equal(x1$n,169)
# expect_equal(x1$restrictions,0)
# expect_equal(x1$est_c, 80)
# expect_equal(x1$p, 6)
# expect_equal(x1$iteration, 5)
#
# expect_match(x1$method, "Smooth transition")
# })
#
# test_that("unrestricted id.st estimation with pre specified c and gamma works 3-dim works without any deterministic term", {
# skip_on_cran()
# set.seed(23211)
# v1 <- vars::VAR(USA, p = 6, ic = "AIC", type = 'none')
# x1 <- id.st(v1, c_fix = 80, gamma_fix = -1)
#
# expect_equal(round(x1$Lik, 4), -518.9424)
# expect_equal(round(sum(diag(x1$Lambda)),4), 0.6292)
# expect_equal(round(sum(x1$B),4), 3.5978)
#
# expect_equal(round(sum(x1$Lambda_SE), 4), 0.1384)
#
# expect_equal(x1$K, 3)
# expect_equal(x1$n,169)
# expect_equal(x1$restrictions,0)
# expect_equal(x1$est_c, 80)
# expect_equal(x1$p, 6)
# expect_equal(x1$iteration, 5)
#
# expect_match(x1$method, "Smooth transition")
# })
#
# test_that("unrestricted id.st estimation with searching algo 3-dim works", {
# skip_on_cran()
# set.seed(23211)
# v1 <- vars::VAR(USA, p = 6, ic = "AIC" )
# cores <- 2
# x1 <- id.st(v1, nc = cores, c_lower = 0.4, c_upper = 0.6, c_step = 5, c_fix = NULL,
# transition_variable = NULL, gamma_lower = -3, gamma_upper = 2,
# gamma_step = 1, gamma_fix = NULL, max.iter = 5,
# crit = 0.01, restriction_matrix = NULL, lr_test = FALSE)
#
# expect_equal(round(x1$Lik, 4), -510.1889)
# expect_equal(round(sum(diag(x1$Lambda)),4), 0.5685)
# expect_equal(round(sum(x1$B),4), 3.6847)
#
# expect_equal(round(sum(x1$Lambda_SE), 4), 0.1256)
#
# expect_equal(x1$K, 3)
# expect_equal(x1$n,169)
# expect_equal(x1$restrictions,0)
# expect_equal(x1$est_c, 73)
# expect_equal(x1$est_g, -1)
# expect_equal(x1$p, 6)
# expect_equal(x1$iteration, 5)
#
# expect_match(x1$method, "Smooth transition")
#
# })
#
# test_that("id.st estimation with restrictions 3-dim works", {
# skip_on_cran()
# set.seed(23211)
# v1 <- vars::VAR(USA, p = 6, ic = "AIC" )
# restmat <- matrix(NA, 3, 3)
# restmat[1, 2:3] <- 0
# restmat[2, 3] <- 0
#
# ## Without lr test
# x1 <- id.st(v1, c_fix = 80, gamma_fix = -1, restriction_matrix = restmat)
#
# expect_equal(round(x1$Lik, 4), -518.5316)
# expect_equal(round(sum(diag(x1$Lambda)), 4), 0.6118)
# expect_equal(round(sum(x1$B), 4), 3.5253)
#
# expect_equal(round(sum(x1$Lambda_SE), 4), 0.1352)
#
# expect_equal(x1$K, 3)
# expect_equal(x1$n,169)
# expect_equal(x1$restrictions, 3)
# expect_equal(x1$est_c, 80)
# expect_equal(x1$p, 6)
# expect_equal(x1$iteration, 5)
#
# expect_match(x1$method, "Smooth transition")
#
# ## With lr test
# x2 <- id.st(v1, c_fix = 80, gamma_fix = -1, restriction_matrix = restmat, lr_test = TRUE)
#
# expect_equal(round(x2$Lik, 4), round(x1$Lik, 4), -518.5316)
# expect_equal(round(sum(diag(x1$Lambda)), 4), round(sum(diag(x2$Lambda)), 4), 0.6118)
# expect_equal(round(sum(x1$B), 4), round(sum(x2$B), 4), 3.5253)
#
# expect_equal(round(sum(x1$Lambda_SE), 4), round(sum(x2$Lambda_SE), 4), 0.1352)
#
# expect_equal(round(x2$lRatioTest[[2]], 3), 0.328)
# })
#
# test_that("Replication of Luetkepohl + Netsunajev 2017 5-dim works", {
# skip_on_cran()
# set.seed(23211)
# v1 <- vars::VAR(LN, p = 3, ic = "AIC" )
#
# x1 <- id.st(v1, c_fix = 167, gamma_fix = -2.77)
#
# expect_equal(round(x1$Lik, 2), -2878.27)
# expect_equal(round(sum(diag(x1$Lambda)), 3), 2.677)
# expect_equal(round(sum(x1$B), 3), 3.263)
#
# #expect_equal(round(sum(x1$Lambda_SE), 3), 0.424)
#
# expect_equal(x1$K, 5)
# expect_equal(x1$n, 447)
# expect_equal(x1$iteration, 5)
#
# expect_match(x1$method, "Smooth transition")
# })
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