% -*- texinfo -*-
% @deftypefn {Function File} {@var{p} =} mvncdf (@var{x}, @var{mu}, @var{sigma})
% @deftypefnx {Function File} {} mvncdf (@var{a}, @var{x}, @var{mu}, @var{sigma})
% @deftypefnx {Function File} {[@var{p}, @var{err}] =} mvncdf (@dots{})
% Compute the cumulative distribution function of the multivariate
% normal distribution.
%
% @subheading Arguments
%
% @itemize @bullet
% @item
% @var{x} is the upper limit for integration where each row corresponds
% to an observation.
%
% @item
% @var{mu} is the mean.
%
% @item
% @var{sigma} is the correlation matrix.
%
% @item
% @var{a} is the lower limit for integration where each row corresponds
% to an observation. @var{a} must have the same size as @var{x}.
% @end itemize
%
% @subheading Return values
%
% @itemize @bullet
% @item
% @var{p} is the cumulative distribution at each row of @var{x} and
% @var{a}.
%
% @item
% @var{err} is the estimated error.
% @end itemize
%
% @subheading Examples
%
% @example
% @group
% x = [1 2];
% mu = [0.5 1.5];
% sigma = [1.0 0.5; 0.5 1.0];
% p = mvncdf (x, mu, sigma)
% @end group
%
% @group
% a = [-inf 0];
% p = mvncdf (a, x, mu, sigma)
% @end group
% @end example
%
% @subheading References
%
% @enumerate
% @item
% Alan Genz and Frank Bretz. Numerical Computation of Multivariate
% t-Probabilities with Application to Power Calculation of Multiple
% Constrasts. @cite{Journal of Statistical Computation and Simulation},
% 63, pages 361-378, 1999.
% @end enumerate
% @end deftypefn