Giles fixing fRegress and intercepts

Author: Giles Hooker

R/fRegress.double.R

@@ -135,9 +135,10 @@ fRegress.double <- function(y, xfdlist, betalist, wt=NULL,
 
   betacoef <- Cmatinv %*% Dmat
 
-  #  compute degrees of freedom measure
-  
-  df <- sum(diag(Zmat %*% Cmatinv %*% t(Zmat)))
+#    df <- sum(diag(Zmat %*% Cmatinv %*% t(Zmat)))
+
+    hatvals = diag(Zmat %*% Cmatinv %*% t(Zmat))
+    df <- sum(hatvals)
 
   #  set up fdPar object for BETAESTFDPAR
 
@@ -186,6 +187,11 @@ fRegress.double <- function(y, xfdlist, betalist, wt=NULL,
   }
   yhatfdobj <- yhatmat
 
+    # Calculate OCV and GCV scores
+
+    OCV = sum( (ymat-yhatmat)^2/(1-hatvals)^2 )
+    GCV = sum( (ymat-yhatmat)^2 )/( (sum(1-hatvals))^2 )
+  
   #  -----------------------------------------------------------------------
   #        Compute pointwise standard errors of regression coefficients
   #               if both y2cMap and SigmaE are supplied.
@@ -246,6 +252,8 @@ fRegress.double <- function(y, xfdlist, betalist, wt=NULL,
          Cmatinv        = Cmatinv,
          wt             = wt,
          df             = df,
+		 GCV			= GCV,
+		 OCV			= OCV,
          y2cMap         = y2cMap,
          SigmaE         = SigmaE,
          betastderrlist = betastderrlist,

R/fRegress.formula.R

@@ -311,7 +311,7 @@ fRegress.formula <- function(y, data=NULL, betalist=NULL,
         if(is.numeric(xfdlist[[i]])) {
           #  if xfdlist[[i]] is numeric, basis is set up using that  of dependent variable y
           if(is.numeric(y)) {
-            bbasis        <- create.constant.basis(trng)
+            bbasis        <- create.constant.basis(c(0,1))
             bfd           <- fd(basisobj=bbasis)
             betalist[[i]] <- fdPar(bfd)
           } else {