% Description:
%
% Create a design matrix for covariate-covariate interactions.
%
% Syntax:
%
% [ X, terms ] = mCC2X(covariates, offset)
%
% Inputs:
%
% covariates - [ N x C ] (double) - columns of quantitative variables
% offset - [ 1 x 1 ] (int) - covariate offset index for terms
% options - [ 1 x P ] (cell) - e.g. { 'verbose' }
% columns - [ T x 2 ] (int) - indices into the columns of covariates
%
% Outputs:
%
% X - [ N x M ] (double)
% terms - [ 1 x M ] (cell)
%
% Details:
%
% Examples:
%
% Notes:
%
% Author(s):
%
% William Gruner (williamgruner@gmail.com)
%
% References:
%
% Acknowledgements:
%
% Many thanks to Dr. Erik Erhardt and Dr. Elena Allen of the Mind Research
% Network (www.mrn.org) for their continued collaboration.
%
% Version:
%
% $Author: William Gruner $
% $Date: 2010-04-08 08:48:31 -0600 (Thu, 08 Apr 2010) $
% $Revision: 490 $
function [ X, terms ] = mCC2X(covariates, offset, options, columns)
if ~exist('offset', 'var') || isempty(offset)
offset = 0;
end
if ~exist('options', 'var')
options = {};
end
if ~exist('columns', 'var')
columns = mNC2(size(covariates, 2));
end
terms = {};
X = [];
if ~isempty(strmatch('verbose', options, 'exact'))
fprintf('\n')
end
for i = 1 : size(columns, 1)
if ~isempty(strmatch('verbose', options, 'exact'))
fprintf('Factor %d%d represents the interaction between columns %d and %d of covariates.\n', ...
columns(i, 1) + offset, columns(i, 2) + offset, ...
columns(i, 1), columns(i, 2))
end
X = cat(2, X, covariates(:, columns(i, 1)) .* covariates(:, columns(i, 2)));
terms{end + 1} = columns(i, :) + offset;
end