www.gusucode.com > mbcmodels 工具箱 matlab 源码程序 > mbcmodels/@xregstatsmodel/pev.m

    function varargout = pev(m, x, varargin)
%PEV Prediction error variance of the model
%    [PEV, Y] = PEV( MODEL, X );
%    X is a(N-by-NF) array, where NF is the number of inputs, and N the
%    number of points to evaluate the model at.
%    To calculate a 95% confidence interval use:
%      yhat = m(X);
%      level = 0.95;
%      ylower = yhat + tinv((1-level)/2,dferror(m))*sqrt(pev(m,X));
%      yupper = yhat - tinv((1-level)/2,dferror(m))*sqrt(pev(m,X));
%
%  See also EvalModel, dferror, predint

%  Copyright 2000-2011 The MathWorks, Inc. and Ford Global Technologies, Inc.

% check the number of inputs and outputs
narginchk(2,inf);
nargoutchk(0,2)

NF = nfactors(m);
if NF==size(x, 2)
    [varargout{1:nargout}] = pev( m.mvModel, x, varargin{:} );
else
    str = '';
    if NF>1
        str = 's';
    end
    error(message('mbc:xregstatsmodel:InvalidSize1', NF, str));
end