v4 matlab: rreplaced beta_rnd.m and gamm_rnd. by GPL'ed custom ones
git-svn-id: https://www.dynare.org/svn/dynare/dynare_v4@1980 ac1d8469-bf42-47a9-8791-bf33cf982152time-shift
sebastien
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8bef1f0399
commit
f76badf151
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@ -1,34 +0,0 @@
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function rnd = beta_rnd (n, a, b)
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% PURPOSE: random draws from the beta(a,b) distribution
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%--------------------------------------------------------------
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% USAGE: rnd = beta_rnd(n,a,b)
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% where: n = size of the vector of draws
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% a = beta distribution parameter, a = scalar
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% b = beta distribution parameter b = scalar
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% NOTE: mean = a/(a+b), variance = ab/((a+b)*(a+b)*(a+b+1))
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%--------------------------------------------------------------
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% RETURNS: n-vector of random draws from the beta(a,b) distribution
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%--------------------------------------------------------------
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% SEE ALSO: beta_d, beta_pdf, beta_inv, beta_rnd
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%--------------------------------------------------------------
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% written by:
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% James P. LeSage, Dept of Economics
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% University of Toledo
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% 2801 W. Bancroft St,
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% Toledo, OH 43606
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% jlesage@spatial-econometrics.com
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if (nargin ~= 3)
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error('Wrong # of arguments to beta_rnd');
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end;
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if any(any((a<=0)|(b<=0)))
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error('Parameter a or b is nonpositive')
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end
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a1n = gamm_rnd(n,a,1);
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a1d = gamm_rnd(n,b,1);
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rnd = a1n./(a1n+a1d);
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@ -0,0 +1,38 @@
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function rnd = betarnd(a, b)
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% BETARND Random samples from the Beta distribution
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% RND = betarnd(A,B) returns a random sample from the
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% Beta distribution with parameters A and B (i.e. mean of
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% the distribution is A/(A+B) and variance is
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% A*B/(A+B)^2/(A+B+1).
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% Copyright (C) 2008 Dynare Team
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%
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% This file is part of Dynare.
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%
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% Dynare is free software: you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation, either version 3 of the License, or
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% (at your option) any later version.
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%
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% Dynare is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
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if (nargin ~= 2)
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error('betarnd: you must give two arguments');
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end
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if (~isscalar(a) || ~isscalar(b))
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error('betarnd: A and B should be scalar parameters');
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end
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if (a <= 0 || a == Inf || b <= 0 || b == Inf)
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rnd = NaN;
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else
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x = gamrnd(a, 1);
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rnd = x/(x+gamrnd(b, 1));
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end
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@ -0,0 +1,57 @@
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function rnd = gamrnd(a,b)
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% GAMRND Random samples from the Gamma distribution
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% RND = gamrnd(A,B) returns a random sample from the
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% Gamma distribution with parameters A and B (i.e. mean of
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% the distribution is A*B and variance is A*B^2).
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%
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% Algorithm of Bauwens, Lubrano & Richard (page 316)
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% Copyright (C) 2006-2008 Dynare Team
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%
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% This file is part of Dynare.
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%
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% Dynare is free software: you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation, either version 3 of the License, or
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% (at your option) any later version.
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%
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% Dynare is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
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if (nargin ~= 2)
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error('gamrnd: you must give two arguments');
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end
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if (~isscalar(a) || ~isscalar(b))
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error('gamrnd: A and B should be scalar parameters');
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end
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if (a <= 0 || a == Inf || b <= 0 || b == Inf)
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rnd = NaN;
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return
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end
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if a >30
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z = randn;
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rnd = b*(z+sqrt(4*a-1))^2/4;
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else
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condi = 1;
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while condi
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x = -1;
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while x<0
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u1 = rand;
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y = tan(pi*u1);
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x = y*sqrt(2*a-1)+a-1;
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end
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u2 = rand;
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if log(u2) <= log(1+y^2)+(a-1)*log(x/(a-1))-y*sqrt(2*a-1);
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break
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end
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end
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rnd = x*b;
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end
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@ -1,72 +0,0 @@
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function gb = gamm_rnd(nrow,m,k)
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% PURPOSE: a matrix of random draws from the gamma distribution
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%---------------------------------------------------
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% USAGE: r = gamm_rnd(n,m,k)
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% where: n = the size of the vector drawn
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% m = a parameter such that the mean of the gamma = m/k
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% k = a parameter such that the variance of the gamma = m/(k^2)
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% note: m=r/2, k=2 equals chisq r random deviate
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%---------------------------------------------------
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% RETURNS:
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% r = an n x 1 vector of random numbers from the gamma distribution
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% --------------------------------------------------
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% SEE ALSO: gamm_inv, gamm_pdf, gamm_cdf
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%---------------------------------------------------
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% NOTE: written by: Michael Gordy, 15 Sept 1993
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% mbgordy@athena.mit.edu
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%---------------------------------------------------
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% REFERENCES: Luc Devroye, Non-Uniform Random Variate Generation,
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% New York: Springer Verlag, 1986, ch 9.3-6.
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if nargin ~= 3
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error('Wrong # of arguments to gamm_rnd');
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end;
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ncol = 1;
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gb=zeros(nrow,ncol);
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if m<=1
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% Use RGS algorithm by Best, p. 426
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c=1/m;
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t=0.07+0.75*sqrt(1-m);
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b=1+exp(-t)*m/t;
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for i1=1:nrow
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for i2=1:ncol
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accept=0;
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while accept==0
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u=rand; w=rand; v=b*u;
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if v<=1
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x=t*(v^c);
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accept=((w<=((2-x)/(2+x))) | (w<=exp(-x)));
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else
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x=-log(c*t*(b-v));
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y=x/t;
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accept=(((w*(m+y-m*y))<=1) | (w<=(y^(m-1))));
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end
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end
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gb(i1,i2)=x;
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end
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end
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else
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% Use Best's rejection algorithm XG, p. 410
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b=m-1;
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c=3*m-0.75;
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for i1=1:nrow
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for i2=1:ncol
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accept=0;
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while accept==0
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u=rand; v=rand;
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w=u*(1-u); y=sqrt(c/w)*(u-0.5);
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x=b+y;
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if x >= 0
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z=64*(w^3)*v*v;
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accept=(z<=(1-2*y*y/x)) ...
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| (log(z)<=(2*(b*log(x/b)-y)));
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end
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end
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gb(i1,i2)=x;
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end
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end
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end
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gb=gb/k;
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@ -108,26 +108,23 @@ for i = 1:npar
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end
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case 2% Gamma prior.
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while condition
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g = gamma_draw(a(i),b(i),p3(i));
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g = gamrnd(a(i),b(i)) + p3(i);
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if g >= bounds(i,1) && g <= bounds(i,2)
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pdraw(i) = g;
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break
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end
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end
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case 1% Beta distribution (TODO: generalized beta distribution)
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case 1% Beta distribution
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while condition
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y1 = gamma_draw(a(i),1,0);
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y2 = gamma_draw(b(i),1,0);
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tmp = y1/(y1+y2);
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tmp = betarnd(a(i), b(i));
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if tmp >= bounds(i,1) && tmp <= bounds(i,2)
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%pdraw(i) = pmean(i)+tmp*pstd(i);
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pdraw(i) = p3(i)+tmp*(p4(i)-p3(i));
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break
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end
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end
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case 4% INV-GAMMA1 distribution
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while condition
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tmp = sqrt(1/gamma_draw(p2(i)/2,2/p1(i),0));
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tmp = sqrt(1/gamrnd(p2(i)/2,2/p1(i)));
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if tmp >= bounds(i,1) && tmp <= bounds(i,2)
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pdraw(i) = tmp;
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break
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@ -135,7 +132,7 @@ for i = 1:npar
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end
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case 6% INV-GAMMA2 distribution
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while condition
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tmp = 1/gamma_draw(p2(i)/2,2/p1(i),0);
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tmp = 1/gamrnd(p2(i)/2,2/p1(i));
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if tmp >= bounds(i,1) && tmp <= bounds(i,2)
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pdraw(i) = tmp;
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break
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@ -145,29 +142,3 @@ for i = 1:npar
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% Nothing to do here.
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end
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end
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function g = gamma_draw(a,b,c)
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% Bauwens, Lubrano & Richard (page 316)
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if a >30
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z = randn;
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g = b*(z+sqrt(4*a-1))^2/4 + c;
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else
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condi = 1;
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while condi
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x = -1;
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while x<0
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u1 = rand;
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y = tan(pi*u1);
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x = y*sqrt(2*a-1)+a-1;
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end
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u2 = rand;
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if log(u2) <= log(1+y^2)+(a-1)*log(x/(a-1))-y*sqrt(2*a-1);
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break
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end
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end
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g = x*b+c;
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end
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@ -11,7 +11,7 @@ function y = rndprior(bayestopt_)
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% SPECIAL REQUIREMENTS
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% none
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% Copyright (C) 2003-2007 Dynare Team
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% Copyright (C) 2003-2008 Dynare Team
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%
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% This file is part of Dynare.
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%
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@ -44,14 +44,14 @@ for i=1:length(pmean),
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stdd = p2(i)/(p4(i)-p3(i));
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A = (1-mu)*mu^2/stdd^2 - mu;
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B = A*(1/mu - 1);
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y(1,i) = beta_rnd(1, A, B);
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y(1,i) = betarnd(A, B);
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y(1,i) = y(1,i) * (p4(i)-p3(i)) + p3(i);
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case 2 %'gamma'
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mu = pmean(i)-p3(i);
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B = mu/p2(i)^2; %gamm_rnd uses 1/B instead of B as param.
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A = mu*B;
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y(1,i) = gamm_rnd(1, A, B) + p3(i);
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B = p2(i)^2/mu;
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A = mu/B;
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y(1,i) = gamrnd(A, B) + p3(i);
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case 3 %'normal'
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MU = pmean(i);
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@ -61,8 +61,7 @@ for i=1:length(pmean),
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case 4 %'invgamma'
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nu = p2(i);
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s = p1(i);
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y(1,i) = 1/sqrt(gamm_rnd(1, nu/2, s/2)); %gamm_rnd uses 1/B
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%instead of B as param.
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y(1,i) = 1/sqrt(gamrnd(nu/2, 2/s));
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case 5 %'uniform'
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y(1,i) = rand*(p2(i)-p1(i)) + p1(i);
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