Nothing
# LUCID - one omics, normal outcome
test_that("check estimations of LUCID with normal outcome (K = 2)", {
# run LUCID model
G <- sim_data$G[1:200, ]
Z <- sim_data$Z[1:200, ]
Y_normal <- sim_data$Y_normal[1:200, ]
cov <- sim_data$Covariate[1:200, ]
X <- sim_data$X[1:200]
# i <- sample(1:2000, 1)
i <- 1008
# cat(paste("test1 - seed =", i, "\n"))
invisible(capture.output(fit1 <- lucid(G = G,
Z = Z,
Y = Y_normal,
CoY = cov,
lucid_model = "early",
family = "normal",
K = 2,
seed = i)))
pars <- fit1
beta_causal <- mean(pars$res_Beta[2, 2:5])
beta_non <- mean(pars$res_Beta[2, 6:10])
mu_causal <- mean(abs(pars$res_Mu[1, 1:5] - pars$res_Mu[2, 1:5]))
mu_non <- mean(abs(pars$res_Mu[1, 6:10] - pars$res_Mu[2, 6:10]))
gamma_causal <- as.numeric(abs(pars$res_Gamma$beta[1] - pars$res_Gamma$beta[2]))
gamma_non <- as.numeric(mean(pars$res_Gamma$beta[3:4]))
sigma <- mean(unlist(fit1$res_Sigma))
# check parameters
expect_equal(beta_causal, log(2), tolerance = 0.2)
expect_equal(beta_non, 0, tolerance = 0.1)
expect_equal(mu_causal, 2, tolerance = 0.1)
expect_equal(mu_non, 0, tolerance = 0.1)
expect_equal(gamma_causal, 1, tolerance = 0.05)
expect_equal(gamma_non, 0, tolerance = 0.05)
expect_equal(sigma, 0.1048542, tolerance = 0.05)
# check summary_lucid
sum_fit1 <- summary_lucid(fit1)
expect_equal(class(fit1), "early_lucid")
expect_equal(class(sum_fit1), "sumlucid_early")
})
test_that("check variable selection on G", {
# run LUCID model
G <- sim_data$G[1:200, ]
Z <- sim_data$Z[1:200, ]
Y_normal <- sim_data$Y_normal[1:200, ]
cov <- sim_data$Covariate[1:200, ]
X <- sim_data$X[1:200]
# i <- sample(1:2000, 1)
i <- 1008
# cat(paste("test2 - seed =", i, "\n"))
invisible(capture.output(fit1 <- lucid(G = G,
Z = Z,
Y = Y_normal,
CoY = cov,
lucid_model = "early",
family = "normal",
K = 2,
seed = i,
Rho_G = 0.05)))
# check parameters
expect_equal(class(fit1$select$selectG), "logical")
expect_equal(as.vector(fit1$select$selectG),
rep(TRUE, 4))
})
test_that("check variable selection on Z", {
# run LUCID model
G <- sim_data$G[1:200, ]
Z <- sim_data$Z[1:200, ]
Y_normal <- sim_data$Y_normal[1:200, ]
cov <- sim_data$Covariate[1:200, ]
X <- sim_data$X[1:200]
# i <- sample(1:2000, 1)
i <- 1008
# cat(paste("test3 - seed =", i, "\n"))
invisible(capture.output(fit1 <- lucid(G = G,
Z = Z,
Y = Y_normal,
CoY = cov,
lucid_model = "early",
family = "normal",
K = 2,
seed = i,
init_par = "random",
Rho_Z_Mu = 13,
Rho_Z_Cov = 0.05)))
# check parameters
expect_equal(class(fit1$select$selectG), "logical")
})
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