calculate MSE of conditional edge predictions and compare to max int

R/conditional_edge_prediction_MSE.R

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+#' @title A Function to calcualte Mean Edgewise MSE to evaluate edge predictions.
+#' @description Calculates mean edgewise MSE for predicted edge values.
+#'
+#' @param edge_prediction_results A list object returned by the
+#' `conditional_edge_prediction()` function.
+#' @return A list of MSE's.
+#' @export
+conditional_edge_prediction_MSE <- function(
+  edge_prediction_results) {
+
+  cur <- edge_prediction_results$max_ent_edge_predictions[,,1]
+  # calculate average MSE
+  dimensions <- ncol(cur)
+  mses <- matrix(NA, ncol = dimensions, nrow = dimensions)
+  mses_max_ent <- mses
+  obv <- edge_prediction_results$observed_network
+
+  for (i in 1:dimensions) {
+    for (j in 1:dimensions) {
+      if (i != j) {
+        cur <- edge_prediction_results$edge_predictions[i,j,]
+        cur2 <- edge_prediction_results$max_ent_edge_predictions[i,j,]
+        mses[i,j] <- mean((cur - obv[i,j])^2)
+        mses_max_ent[i,j] <- mean((cur2 - obv[i,j])^2)
+      }
+    }
+  }
+
+  mse_predicted <- mean(c(mses), na.rm = TRUE)
+  mse_max_ent <- mean(c(mses_max_ent), na.rm = TRUE)
+
+  mse1 <- round(mse_predicted,4)
+  mse2 <- round(mse_max_ent,4)
+  cat("Mean MSE for Predicted Edge Values:", mse1,"\n")
+  cat("Mean MSE for Max Ent Predicted Edge Values:", mse2,"\n")
+
+  reduction <- (1 - mse1/mse2)
+  cat("This represents a",round(reduction*100,2),
+      "percent reduction in the average edgewise MSE when using the GERGM model.\n")
+
+  return(list(model_prediction_average_MSE = mse1,
+              max_ent_prediction_average_MSE = mse2))
+}
+