## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup-------------------------------------------------------------------- library(MUGS) ## ----load_data---------------------------------------------------------------- # Load required data data(S.1) data(S.2) data(X.group.source) data(X.group.target) data(U.1) data(U.2) ## ----prepare_variables-------------------------------------------------------- # Set parameters n1 <- 100 n2 <- 100 p <- 5 # Ensure row and column names are consistent for matching rownames(U.1) <- as.character(seq_len(nrow(U.1))) # "1" to "100" rownames(U.2) <- as.character(seq(from = 51, length.out = nrow(U.2))) # "51" to "150" # Align S.1 and S.2 with embeddings rownames(S.1) <- rownames(U.1) colnames(S.1) <- rownames(U.1) rownames(S.2) <- rownames(U.2) colnames(S.2) <- rownames(U.2) # Get common codes names.list.1 <- rownames(S.1) names.list.2 <- rownames(S.2) common_codes <- intersect(names.list.1, names.list.2) n.common <- length(common_codes) if (n.common == 0) stop("Error: No common codes found between source and target sites.") full.name.list <- c(names.list.1, names.list.2) # Initialize delta matrix delta.int <- matrix(0, length(full.name.list), p) rownames(delta.int) <- full.name.list ## ----run_function------------------------------------------------------------- # Estimate site-specific effects CodeSiteEff_l2_par.out <- CodeSiteEff_l2_par( S.1 = S.1, S.2 = S.2, n1 = 100, n2 = 100, U.1 = U.1, U.2 = U.2, V.1= U.1, V.2 = U.2, delta.int = delta.int, lambda.delta = 3000, p=5, common_codes = common_codes, n.common = 50, n.core=2) ## ----examine_output----------------------------------------------------------- # View structure of the output str(CodeSiteEff_l2_par.out) # Print specific components of the result cat("\nEstimated Effects (Delta):\n") print(CodeSiteEff_l2_par.out$delta[1:5, 1:5]) # First 5 rows and columns of delta matrix cat("\nRegularization Path:\n") print(CodeSiteEff_l2_par.out$path)