# 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))) sum_fit1 = summary_lucid(fit1) print.sumlucid(sum_fit1) 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", seed = i, useY = TRUE))) sum_fit2 = summary_lucid(fit2) print.sumlucid(sum_fit2) 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, CoG = CoG, CoY = CoY, useY = TRUE))) sum_fit3 = summary_lucid(fit3) print.sumlucid(sum_fit3) })