fix to unit test for M1 mac

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: tsgarch
 Type: Package
 Title: Univariate GARCH Models
-Version: 1.0.1
+Version: 1.0.2
 Authors@R: c(person("Alexios", "Galanos", role = c("aut", "cre","cph"), email = "alexios@4dscape.com"))
 Maintainer: Alexios Galanos <alexios@4dscape.com>
 Depends: R (>= 3.5.0), methods, tsmethods

NEWS.md

@@ -1,3 +1,8 @@
+# tsgarch 1.0.2
+
+* Moved a unit tests back to original folder and added a tolerance
+to the expectation per CRAN maintainers directions.
+
 # tsgarch 1.0.1
 
 * Moved a couple of unit tests to other folder to avoid checking on CRAN

tests/testthat/test-simulation.R

@@ -141,4 +141,72 @@ test_that("cgarch(1,1) simulation: validate algoritm",{
     expect_equal(sim$sigma[1,], local_mod_cgarch$sigma)
 })
 
+test_that("cgarch(2,1) simulation: validate algoritm",{
+    local_spec_cgarch <- garch_modelspec(y[1:1800,1], constant = TRUE, model = "cgarch",
+                                         order = c(2,1), vreg = y[1:1800,2],
+                                         distribution = "norm")
+    local_mod_cgarch <- suppressWarnings(estimate(local_spec_cgarch))
+    spec <- copy(local_spec_cgarch)
+    spec$parmatrix <- copy(local_mod_cgarch$parmatrix)
+    v <- c(as.numeric(y[1:1800,2]) * coef(local_mod_cgarch)["xi1"])
+    z <- matrix(as.numeric(residuals(local_mod_cgarch, standardize = TRUE)), nrow = 1)
+    sim <- simulate(spec, nsim = 1, h = length(spec$target$y_orig),
+                    var_init = rep(global_mod_cgarch$var_initial,2),
+                    innov = z, vreg = v)
+    expect_equal(sim$sigma[1,], local_mod_cgarch$sigma, tolerance = 1e-6)
+
+})
+
+test_that("egarch(1,1) simulation: validate algoritm",{
+    spec <- copy(global_spec_garch)
+    spec$parmatrix <- copy(global_mod_garch$parmatrix)
+    v <- c(as.numeric(y[1:1800,2]) * coef(global_mod_garch)["xi1"])
+    z <- matrix(as.numeric(residuals(global_mod_garch, standardize = TRUE)), nrow = 1)
+    # use fixed innovation and replicate the initial conditions to guarantee a deterministic
+    # simulation which serves to validate the algorithm for correctness and reproducability
+    sim <- simulate(spec, nsim = 1, h = length(spec$target$y_orig),
+                    var_init = global_mod_garch$var_initial,
+                    innov = z, vreg = v,
+                    arch_initial = global_mod_garch$arch_initial)
+    expect_equal(sim$sigma[1,], global_mod_garch$sigma, tolerance = 1e-6)
+})
 
+test_that("simulate norm: same seed same output",{
+    spec <- copy(global_spec_garch)
+    spec$parmatrix <- copy(global_mod_garch$parmatrix)
+    maxpq <- max(spec$model$order)
+    v_init <- as.numeric(tail(sigma(global_mod_garch)^2, maxpq))
+    i_init <- as.numeric(tail(residuals(global_mod_garch),maxpq))
+    simulate_spec1 <- simulate(spec, nsim = 100, seed = 101, h = 10, var_init = v_init,
+                               innov_init = i_init, vreg = y[1801:1810,2])
+    simulate_spec2 <- simulate(spec, nsim = 100, seed = 101, h = 10, var_init = v_init,
+                               innov_init = i_init, vreg = y[1801:1810,2])
+    expect_equal(simulate_spec1$series,simulate_spec2$series, tolerance = 1e-6)
+    expect_equal(NROW(simulate_spec1$series),100)
+    expect_equal(NCOL(simulate_spec1$series),10)
+    expect_s3_class(simulate_spec1, class = "tsgarch.simulate")
+    expect_s3_class(simulate_spec1$sigma, class = "tsmodel.distribution")
+})
+
+test_that("simulate ghst: same seed same output",{
+    spec <- global_spec_garch_jsu
+    spec$parmatrix <- copy(global_mod_garch_jsu$parmatrix)
+    maxpq <- max(spec$model$order)
+    v_init <- as.numeric(tail(sigma(global_mod_garch_jsu)^2, maxpq))
+    i_init <- as.numeric(tail(residuals(global_mod_garch_jsu),maxpq))
+    simulate_spec1 <- simulate(spec, nsim = 100, seed = 101, h = 10, var_init = v_init,
+                               innov_init = i_init, vreg = y[1801:1810,2])
+    simulate_spec2 <- simulate(spec, nsim = 100, seed = 101, h = 10, var_init = v_init,
+                               innov_init = i_init, vreg = y[1801:1810,2])
+    expect_equal(simulate_spec1$series,simulate_spec2$series, tolerance = 1e-6)
+})
+
+test_that("simulation: long run variance check",{
+    spec_garch <- garch_modelspec(y = y[1:1800,1], constant = TRUE, model = "garch")
+    sim <- simulate(spec_garch, nsim = 1, h = 25000, seed = 77, burn = 100)
+    expect_equal(mean(sim$sigma[1,]^2), unconditional(spec_garch), tolerance = 0.01)
+    spec_egarch <- garch_modelspec(y = y[1:1800,1], constant = TRUE, model = "egarch")
+    sim <- simulate(spec_egarch, nsim = 1, h = 25000, seed = 727, burn = 100)
+    expect_equal(mean(sim$sigma[1,]^2), unconditional(spec_egarch), tolerance = 0.1)
+
+})