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## Copyright (C) 2008 Jonathan Stickel <jonathan.stickel@nrel.gov>
##
## This program is free software; you can redistribute it and/or modify it under
## the terms of the GNU General Public License as published by the Free Software
## Foundation; either version 3 of the License, or (at your option) any later
## version.
##
## This program is distributed in the hope that it will be useful, but WITHOUT
## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
## details.
##
## You should have received a copy of the GNU General Public License along with
## this program; if not, see <http://www.gnu.org/licenses/>.
## -*- texinfo -*-
## @deftypefn {Function File} {@var{cve} =} rgdtsmcorewrap (@var{log10lambda}, @var{x}, @var{y}, @var{d}, @var{mincell}, @var{options})
## @deftypefnx {Function File} {@var{stdevdif} =} rgdtsmcorewrap (@var{log10lambda}, @var{x}, @var{y}, @var{d}, @var{mincell}, @var{options})
##
## Wrapper function for rgdtsmcore in order to minimize over
## @var{lambda} w.r.t. cross-validation error OR the squared difference
## between the standard deviation of (@var{y}-@var{yhat}) and the given
## standard deviation. This function is called from regdatasmooth.
## @seealso{regdatasmooth}
## @end deftypefn
function out = rgdtsmcorewrap (log10lambda, x, y, d, mincell, varargin)
if (nargin < 5)
print_usage;
endif
lambda = 10^(log10lambda);
if ( length(mincell) == 2 ) # using stdev to find optimal lambda
stdev = mincell{2};
yhat = rgdtsmcore (x, y, d, lambda, varargin{:});
xhatprov = 0;
relative = 0;
for i = 1:length(varargin)
if strcmp(varargin{i},"relative")
relative = 1;
elseif strcmp(varargin{i},"xhat")
xhatprov = 1;
xhat = varargin{i+1};
endif
endfor
if (xhatprov)
idx = interp1(xhat,1:length(xhat),x,"nearest");
if relative
stdevd = std((y-yhat(idx))./y);
else
stdevd = std(y-yhat(idx));
endif
else
if (relative)
stdevd = std((y-yhat)./y);
else
stdevd = std(y-yhat);
endif
endif
out = (stdevd - stdev)^2;
else # use gcv to find optimal lambda
[yhat, out] = rgdtsmcore (x, y, d, lambda, varargin{:});
endif
endfunction
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