gmm_1 <- list(alpha = c(0.4, 0.6), mu = matrix(c(2, 0, 3, 1), 2, dimnames = list(c("B", "A"), NULL)), sigma = list(matrix(c(2, 1, 1, 1), 2, dimnames = list(c("B", "A"), c("B", "A"))), matrix(c(5, 3, 3, 2), 2, dimnames = list(c("B", "A"), c("B", "A"))))) class(gmm_1) <- "gmm" gmm_2 <- list(alpha = c(0.4, 0.6), mu = matrix(c(0, 1), 1, dimnames = list("A", NULL)), sigma = list(matrix(1, dimnames = list("A", "A")), matrix(2, dimnames = list("A", "A")))) class(gmm_2) <- "gmm" gmm_3 <- list(alpha = c(0.4, 0.6), mu = matrix(c(2, 0, 3, 1), 2, dimnames = list(c("B", "A.1"), NULL)), sigma = list(matrix(c(2, 1, 1, 1), 2, dimnames = list(c("B", "A.1"), c("B", "A.1"))), matrix(c(5, 3, 3, 2), 2, dimnames = list(c("B", "A.1"), c("B", "A.1"))))) class(gmm_3) <- "gmm" gmbn_1 <- list(A = gmm_2, B = gmm_1) class(gmbn_1) <- "gmbn" gmbn_2 <- list(A = gmm_2, B = gmm_3) class(gmbn_2) <- "gmbn" gmdbn_1 <- list(b_1 = gmbn_1, b_2 = gmbn_1) class(gmdbn_1) <- "gmdbn" gmdbn_2 <- list(b_1 = gmbn_1, b_2 = gmbn_2) class(gmdbn_2) <- "gmdbn" test_that("compute the AIC of a gmm object", { expect_equal(AIC(gmm_1, data.frame(A = c(0, 3, 6, 9), B = c(4, 7, 1, 6))), - 121.1373, tolerance = 0.01) expect_equal(AIC(gmm_1, matrix(c(0, 3, 6, 9, 4, 7, 1, 6), 4, dimnames = list(NULL, c("A", "B")))), - 121.1373, tolerance = 0.01) }) test_that("compute the AIC of a gmm object with missing values", { expect_equal(AIC(gmm_1, data.frame(A = c(0, 3, NA, NA), B = c(4, 7, 1, NA))), as.numeric(NA)) }) test_that("compute the AIC of a gmm object with extra columns", { expect_equal(AIC(gmm_1, data.frame(A = c(0, 3, 6, 9), B = c(4, 7, 1 , 6), C = c(0, 0, 0, 0))), - 121.1373, tolerance = 0.01) }) test_that("compute the AIC of a gmm object with no row", { expect_equal(AIC(gmm_1, data.frame(A = numeric(), B = numeric())), - 11.05) expect_equal(AIC(gmm_1, data.frame(A = logical(), B = logical())), - 11.05) }) test_that("compute the non-regularized AIC of a gmm object", { expect_equal(AIC(gmm_1, data.frame(A = c(0, 3, 6, 9), B = c(4, 7, 1, 6)), regul = NULL), - 121.0873, tolerance = 0.01) }) test_that("compute the conditional AIC of a gmm object", { expect_equal(AIC(gmm_1, data.frame(A = c(0, 3, 6, 9), B = c(4, 7, 1, 6)), y = "B"), - 91.30329, tolerance = 0.01) }) test_that("compute the AIC of a gmbn object", { expect_equal(AIC(gmbn_1, data.frame(A = c(0, 3, 6, 9), B = c(4, 7, 1, 6))), list(global = - 126.0873, local = c(A = - 34.78401, B = - 91.30329)), tolerance = 0.01) }) test_that("compute the AIC of a gmbn object with missing values", { expect_equal(AIC(gmbn_1, data.frame(A = c(0, 3, NA, NA), B = c(4, 7, 1, NA))), list(global = as.numeric(NA), local = c(A = as.numeric(NA), B = as.numeric(NA)))) }) test_that("compute the AIC of a gmbn object with extra columns", { expect_equal(AIC(gmbn_1, data.frame(A = c(0, 3, 6, 9), B = c(4, 7, 1, 6), C = c(0, 0, 0, 0))), list(global = - 126.0873, local = c(A = - 34.78401, B = - 91.30329)), tolerance = 0.01) }) test_that("compute the AIC of a gmbn object with no row", { expect_equal(AIC(gmbn_1, data.frame(A = numeric(), B = numeric())), list(global = - 16, local = c(A = - 5, B = - 11))) expect_equal(AIC(gmbn_1, data.frame(A = logical(), B = logical())), list(global = - 16, local = c(A = - 5, B = - 11))) }) test_that("compute the AIC of a temporal gmbn object with one observation sequence", { expect_equal(AIC(gmbn_2, data.frame(A = c(0, 3, 6, 9), B = c(4, 7, 1, 6))), list(global = - 85.80351, local = c(A = - 33.55093, B = - 52.25258)), tolerance = 0.01) expect_equal(AIC(gmbn_2, data.frame(A = c(0, 3, 6, 9), B = c(4, 7, 1, 6)), col_seq = character()), list(global = - 85.80351, local = c(A = - 33.55093, B = - 52.25258)), tolerance = 0.01) }) test_that("compute the AIC of a temporal gmbn object with several observation sequences", { expect_equal(AIC(gmbn_2, data.frame(seq = c(1, 1, 2, 2), A = c(0, 3, 6, 9), B = c(4, 7, 1, 6)), col_seq = "seq"), list(global = - 65.27128, local = c(A = -25.5246, B = -39.74667)), tolerance = 0.01) }) test_that("compute the AIC of a temporal gmbn object with duplicated observation sequence column names", { expect_equal(AIC(gmbn_2, data.frame(seq = c(1, 1, 2, 2), A = c(0, 3, 6, 9), B = c(4, 7, 1, 6)), col_seq = c("seq", "seq")), list(global = - 65.27128, local = c(A = -25.5246, B = -39.74667)), tolerance = 0.01) }) test_that("compute the AIC of a gmdbn object with non-temporal gmbn elements", { expect_equal(AIC(gmdbn_1, data.frame(seq = c(1, 1, 2, 2), A = c(0, 3, 6, 9), B = c(4, 7, 1, 6)), col_seq = "seq"), list(global = - 142.0873, local = list(b_1 = c(A = - 14.25941, B = - 51.7324), b_2 = c(A = - 25.5246, B = - 50.57089))), tolerance = 0.01) }) test_that("compute the AIC of a gmdbn object with temporal gmbn elements", { expect_equal(AIC(gmdbn_2, data.frame(seq = c(1, 1, 2, 2), A = c(0, 3, 6, 9), B = c(4, 7, 1, 6)), col_seq = "seq"), list(global = - 131.2631, local = list(b_1 = c(A = - 14.25941, B = - 51.7324), b_2 = c(A = - 25.5246, B = - 39.74667))), tolerance = 0.01) })