Nothing
# LUCID - LUCID in Serial, binary outcome
test_that("check estimations of LUCID in Serial with binary outcome (K = 2,2,2,2,2)", {
i <- 1008
set.seed(i)
G <- matrix(rnorm(500), nrow = 100)
Z1 <- matrix(rnorm(1000),nrow = 100)
Z2 <- matrix(rnorm(1000), nrow = 100)
Z3 <- matrix(rnorm(1000), nrow = 100)
Z4 <- matrix(rnorm(1000), nrow = 100)
Z5 <- matrix(rnorm(1000), nrow = 100)
Z <- list(Z1 = Z1, Z2 = Z2, Z3 = Z3, Z4 = Z4, Z5 = Z5)
Y <- rbinom(n=100, size =1, prob =0.25)
CoY <- matrix(rnorm(200), nrow = 100)
CoG <- matrix(rnorm(200), nrow = 100)
# i <- sample(1:2000, 1)
# cat(paste("test1 - seed =", i, "\n"))
invisible(capture.output(fit1 <- estimate_lucid(G = G, Z = Z, Y = Y, K = c(2, 2, 2, 2, 2),
lucid_model = "serial",
family = "binary",
init_omic.data.model = "VVV",
CoG = CoG, CoY = CoY,
seed = i,
useY = TRUE)))
betas <- mean(unlist(fit1$res_Beta))
mus <- mean(unlist(fit1$res_Mu))
sigma <- mean(unlist(fit1$res_Sigma))
Gamma <- mean(unlist(fit1$res_Gamma))
# check parameters
expect_equal(betas, -0.0672, tolerance = 0.01)
expect_equal(mus, 0.0189, tolerance = 0.01)
expect_equal(sigma, 0.086, tolerance = 0.01)
expect_equal(Gamma, -0.164, tolerance = 0.01)
expect_equal(class(fit1), "lucid_serial")
Z <- list(Z1 = Z1, list(Z2 = Z2, Z3 = Z3), Z4 = Z4, Z5 = Z5)
invisible(capture.output(fit2 <- estimate_lucid(G = G, Z = Z, Y = Y, K = list(2,list(2,2),2,2),
CoG = CoG, CoY = CoY,
lucid_model = "serial",
family = "binary",
init_omic.data.model = "VVV",
seed = i,
useY = TRUE)))
betas <- mean(unlist(fit2$res_Beta))
mus <- mean(unlist(fit2$res_Mu))
sigma <- mean(unlist(fit2$res_Sigma))
Gamma <- mean(unlist(fit2$res_Gamma))
# check parameters
expect_equal(betas, -0.0672, tolerance = 0.01)
expect_equal(mus, 0.01795, tolerance = 0.01)
expect_equal(sigma, 0.0863, tolerance = 0.01)
expect_equal(Gamma, -0.164, tolerance = 0.01)
expect_equal(class(fit2), "lucid_serial")
Z <- list(Z1 = Z1, list(Z2 = Z2, Z3 = Z3), list(Z4 = Z4, Z5 = Z5))
invisible(capture.output(fit3 <- estimate_lucid(G = G, Z = Z, Y = Y, K = list(3,list(2,2),list(2,2)),
lucid_model = "serial",
family = "binary",
seed = i,
init_omic.data.model = "VVV",
CoG = CoG, CoY = CoY,
useY = TRUE)))
betas <- mean(unlist(fit3$res_Beta))
mus <- mean(unlist(fit3$res_Mu))
sigma <- mean(unlist(fit3$res_Sigma))
Gamma <- mean(unlist(fit3$res_Gamma$Gamma$mu))
# check parameters
expect_equal(betas, -7.73, tolerance = 0.01)
expect_equal(mus, 0.01496, tolerance = 0.01)
expect_equal(sigma, 0.0877, tolerance = 0.01)
expect_equal(Gamma, 0.25, tolerance = 0.01)
expect_equal(class(fit3), "lucid_serial")
})
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