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function r = betarnd(a,b,m,n);
%BETARND Random matrices from beta distribution.
% R = BETARND(A,B) returns a matrix of random numbers chosen
% from the beta distribution with parameters A and B.
% The size of R is the common size of A and B if both are matrices.
% If either parameter is a scalar, the size of R is the size of the other
% parameter. Alternatively, R = BETARND(A,B,M,N) returns an M by N matrix.
% Reference:
% [1] L. Devroye, "Non-Uniform Random Variate Generation",
% Springer-Verlag, 1986
% Copyright (c) 1993-98 by The MathWorks, Inc.
% $Revision: 1.1.1.1 $ $Date: 2005/04/26 02:29:18 $
if nargin < 2,
error('Requires at least two input arguments');
end
if nargin == 2
[errorcode rows columns] = rndcheck(2,2,a,b);
end
if nargin == 3
[errorcode rows columns] = rndcheck(3,2,a,b,m);
end
if nargin == 4
[errorcode rows columns] = rndcheck(4,2,a,b,m,n);
end
if errorcode > 0
error('Size information is inconsistent.');
end
r = zeros(rows,columns);
% Use Theorem 4.1, case A (Devroye, page 430) to derive beta
% random numbers as a ratio of gamma random numbers.
if prod(size(a)) == 1
a1 = a(ones(rows,1),ones(columns,1));
g1 = gamrnd(a1,1);
else
g1 = gamrnd(a,1);
end
if prod(size(b)) == 1
b1 = b(ones(rows,1),ones(columns,1));
g2 = gamrnd(b1,1);
else
g2 = gamrnd(b,1);
end
r = g1 ./ (g1 + g2);
% Return NaN if b is not positive.
if any(any(b <= 0));
if prod(size(b) == 1)
tmp = NaN;
r = tmp(ones(rows,columns));
else
k = find(b <= 0);
tmp = NaN;
r(k) = tmp(ones(size(k)));
end
end
% Return NaN if a is not positive.
if any(any(a <= 0));
if prod(size(a) == 1)
tmp = NaN;
r = tmp(ones(rows,columns));
else
k = find(a <= 0);
tmp = NaN;
r(k) = tmp(ones(size(k)));
end
end
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