/usr/share/octave/packages/statistics-1.3.0/iwishrnd.m is in octave-statistics 1.3.0-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 | ## Copyright (C) 2013 Nir Krakauer <nkrakauer@ccny.cuny.edu>
##
## 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.
##
## Octave 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 Octave; see the file COPYING. If not, see <http://www.gnu.org/licenses/>.
## -*- texinfo -*-
## @deftypefn {Function File} {} [@var{W}[, @var{DI}]] = iwishrnd (@var{Psi}, @var{df}[, @var{DI}][, @var{n}=1])
## Return a random matrix sampled from the inverse Wishart distribution with given parameters
##
## Inputs: the @var{p} x @var{p} positive definite matrix @var{Tau} and scalar degrees of freedom parameter @var{df} (and optionally the transposed Cholesky factor @var{DI} of @var{Sigma} = @code{inv(Tau)}).
## @var{df} can be non-integer as long as @var{df} > @var{d}
##
## Output: a random @var{p} x @var{p} matrix @var{W} from the inverse Wishart(@var{Tau}, @var{df}) distribution. (@code{inv(W)} is from the Wishart(@code{inv(Tau)}, @var{df}) distribution.) If @var{n} > 1, then @var{W} is @var{p} x @var{p} x @var{n} and holds @var{n} such random matrices. (Optionally, the transposed Cholesky factor @var{DI} of @var{Sigma} is also returned.)
##
## Averaged across many samples, the mean of @var{W} should approach @var{Tau} / (@var{df} - @var{p} - 1).
##
## Reference: Yu-Cheng Ku and Peter Bloomfield (2010), Generating Random Wishart Matrices with Fractional Degrees of Freedom in OX, http://www.gwu.edu/~forcpgm/YuChengKu-030510final-WishartYu-ChengKu.pdf
##
## @seealso{wishrnd, iwishpdf}
## @end deftypefn
## Author: Nir Krakauer <nkrakauer@ccny.cuny.edu>
## Description: Random matrices from the inverse Wishart distribution
function [W, DI] = iwishrnd(Tau, df, DI, n = 1)
if (nargin < 2)
print_usage ();
endif
if nargin < 3 || isempty(DI)
try
D = chol(inv(Tau));
catch
error('Cholesky decomposition failed; Tau probably not positive definite')
end_try_catch
DI = D';
else
D = DI';
endif
w = wishrnd([], df, D, n);
if n > 1
p = size(D, 1);
W = nan(p, p, n);
endif
for i = 1:n
W(:, :, i) = inv(w(:, :, i));
endfor
endfunction
%!assert(size (iwishrnd (1,2,1)), [1, 1]);
%!assert(size (iwishrnd ([],2,1)), [1, 1]);
%!assert(size (iwishrnd ([3 1; 1 3], 2.00001, [], 1)), [2, 2]);
%!assert(size (iwishrnd (eye(2), 2, [], 3)), [2, 2, 3]);
%% Test input validation
%!error iwishrnd ()
%!error iwishrnd (1)
%!error iwishrnd ([-3 1; 1 3],1)
%!error iwishrnd ([1; 1],1)
|