library("batchtools") library("rstanmed") dir <- paste0(getwd(), "/") # Registries for storing simulation replicates ---------------------------- # Bayesian data fusion results bdf_reg_1p5 <- batchtools::makeRegistry(file.dir = paste0(dir, "registry_b_1p5/"), packages = "rstanmed", make.default = FALSE) bdf_reg_0_1p5 <- batchtools::makeRegistry(file.dir = paste0(dir, "registry_b_0_1p5/"), packages = "rstanmed", make.default = FALSE) # Frequentist correction factor results frq_reg_1p5 <- batchtools::makeRegistry(file.dir = paste0(dir, "registry_f_1p5/"), packages = "rstanmed", make.default = FALSE) frq_reg_0_1p5 <- batchtools::makeRegistry(file.dir = paste0(dir, "registry_f_0_1p5/"), packages = "rstanmed", make.default = FALSE) nreps <- 200 # nreps <- 10 nonseq_multiplier <- c(32, 45) # used to make non-sequential seeds # Submitting BDF simulation replicates ------------------------------------ submit_bdf_jobs(registry = bdf_reg_1p5, transport = TRUE, seed = (1:nreps)*nonseq_multiplier[1], clear_existing = FALSE, u_ei = 0:1, am_intx = 0:1, n = c(1500, 5000, 10000), result_type = "processed", iter = 2000, chains = 4, n_ratio = 10) submit_bdf_jobs(registry = bdf_reg_0_1p5, transport = FALSE, seed = (1:nreps)*nonseq_multiplier[2], clear_existing = FALSE, u_ei = 0:1, am_intx = 0:1, n = c(1500, 5000, 10000), result_type = "processed", iter = 2000, chains = 4, n_ratio = 10) # Submitting frequentist simulation replicates ---------------------------- submit_frequentist_jobs(registry = frq_reg_1p5, transport = TRUE, seed = (1:nreps)*nonseq_multiplier[1], clear_existing = FALSE, u_ei = 0:1, am_intx = 0:1, n = c(1500, 5000, 10000), result_type = "processed", B = 200, n_ratio = 10) submit_frequentist_jobs(registry = frq_reg_0_1p5, transport = FALSE, seed = (1:nreps)*nonseq_multiplier[2], clear_existing = FALSE, u_ei = 0:1, am_intx = 0:1, n = c(1500, 5000, 10000), result_type = "processed", B = 200, n_ratio = 10)