| gcval | R Documentation | 
Extract the smallest regularization parameter.
gcval(U, s, b, npoints)
| U | U matrix from gsvd(G, L) | 
| s | [diag(C) diag(S)] which are the lambdas and mus from the gsvd | 
| b | the data to try and match | 
| npoints | number of alphas to estimate | 
Evaluate the GCV function gcv_function at npoints points.
List:
| reg_min | alpha with the minimal g (scalar) | 
| g  | || Gm_(alpha,L) - d ||^2 / (Tr(I - GG#)^2 | 
| alpha | alpha for the corresponding g | 
Jonathan M. Lees<jonathan.lees@unc.edu>
gcv_function
set.seed(2015)
VSP = vspprofile()
t = VSP$t2
G = VSP$G
M = VSP$M
N = VSP$N
L1 = get_l_rough(N,1);
littleU = PEIP::GSVD(as.matrix(G), as.matrix(L1) );
BIGU = flipGSVD(littleU, dim(G), dim(L1) )
U1 = BIGU$U
V1 =BIGU$V
X1=BIGU$X
Lam1=BIGU$C
M1=BIGU$S
lam=sqrt(diag(t(Lam1 %*% Lam1)));
mu=sqrt(diag(t(M1)%*%M1));
p=rnk(L1);
sm1=cbind(lam[1:p],mu[1:p])
### % get the gcv values varying alpha
###
ngcvpoints=1000;
HI = gcval(U1,sm1,t,ngcvpoints);
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