function Theta = boot_GMt(rep,U,V,lambdas,nu,weight,alpha)
%function Tboot = boot_GMt(rep,U,V,l,nu,wgt,trp)
%  Residual-bootstrapped GMt functional regression estimator
%
% INPUT
%   rep (scalar)    Number of bootstrap replications
%   U   (n x p)     Reduced-rank standardized component scores of X
%   V   (n x p)     Reduced-rank standardized component scores of Y
%   l   (p x 1)     Eigenvalues of PCs of X
%   nu  (scalar)    Degrees of freedom of the t used as loss function
%   wgt (char)      Trimming type: "metric" or "rank"
%   trp (scalar)    Trimming proportion (between 0 and 1)
%
% OUTPUT
%   Tboot  (p x q x rep)   Bootsrap replications of regression estimator


[n,p] = size(U);
q = size(V,2);
T0 = treg(U,V,lambdas,nu,weight,alpha,'off');
R = V-U*T0;
Theta = zeros(p,q,rep);
for i = 1:rep
    iboot = randi(n,[n 1]);
    Vboot = U*T0 + R(iboot,:);
    Theta(:,:,i) = treg(U,Vboot,lambdas,nu,weight,alpha,'off');
end