From 25b20984d5bf92cd04a7a3cac7b5e893b9761b64 Mon Sep 17 00:00:00 2001
From: daniel <daniel@kapla.at>
Date: Wed, 10 Feb 2021 18:54:40 +0100
Subject: [PATCH] fix: predict_dim_cv always failes with dim. missmatch, add:
 support for central method in predcit_dim_cv

---
 CVE/R/predict_dim.R | 19 ++++++++++++-------
 1 file changed, 12 insertions(+), 7 deletions(-)

diff --git a/CVE/R/predict_dim.R b/CVE/R/predict_dim.R
index e5e38f2..64bcee3 100644
--- a/CVE/R/predict_dim.R
+++ b/CVE/R/predict_dim.R
@@ -7,8 +7,8 @@ predict_dim_cv <- function(object) {
     Sigma_root <- eig$vectors %*% tcrossprod(diag(sqrt(eig$values)), eig$vectors)
     X <- X %*% solve(Sigma_root)
 
-    pred <- matrix(0, n, length(object$res))
-    colnames(pred) <- names(object$res)
+    pred <- array(0, c(n, ncol(object$Fy), length(object$res)),
+                  dimnames = list(NULL, NULL, names(object$res)))
     for (dr.k in object$res) {
         # get "name" of current dimension
         k <- as.character(dr.k$k)
@@ -16,12 +16,11 @@ predict_dim_cv <- function(object) {
         X.proj <- X %*% dr.k$B
 
         for (i in 1:n) {
-            model <- mda::mars(X.proj[-i, ], object$Y[-i])
-            pred[i, k] <- predict(model, X.proj[i, , drop = F])
+            model <- mda::mars(X.proj[-i, ], object$Fy[-i, ])
+            pred[i, , k] <- predict(model, X.proj[i, , drop = FALSE])
         }
-
     }
-    MSE <- colMeans((pred - object$Y)^2)
+    MSE <- apply((pred - as.numeric(object$Fy))^2, 3, mean)
 
     return(list(
         MSE = MSE,
@@ -30,6 +29,9 @@ predict_dim_cv <- function(object) {
 }
 
 predict_dim_elbow <- function(object) {
+    if (ncol(object$Fy) > 1) # TODO: Implement or find better way
+        stop("For multivariate or central models not supported yet.")
+
     # extract original data from object (cve result)
     X <- object$X
     Y <- object$Y
@@ -71,6 +73,9 @@ predict_dim_elbow <- function(object) {
 }
 
 predict_dim_wilcoxon <- function(object, p.value = 0.05) {
+    if (ncol(object$Fy) > 1) # TODO: Implement or find better way
+        stop("For multivariate or central models not supported yet.")
+
     # extract original data from object (cve result)
     X <- object$X
     Y <- object$Y
@@ -164,7 +169,7 @@ predict_dim_wilcoxon <- function(object, p.value = 0.05) {
 #' y <- x %*% B + 0.25 * rnorm(100)
 #'
 #' # Calculate cve for unknown k between min.dim and max.dim.
-#' cve.obj.simple <- cve(y ~ x) 
+#' cve.obj.simple <- cve(y ~ x)
 #'
 #' predict_dim(cve.obj.simple)
 #'