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beta.cpp
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// This program, BayeScan, aims at detecting genetics markers under selection,
// based on allele frequency differences between population.
// Copyright (C) 2010 Matthieu Foll
//
// 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.
//
// This program 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 this program. If not, see <http://www.gnu.org/licenses/>.
#include <stdio.h>
#include <math.h>
#include <stdlib.h>
#include "global_defs.h"
#define ABS(x) ((x) >= 0 ? (x) : -(x))
#define minRnd(a,b) ((a) <= (b) ? (a) : (b))
#define maxRnd(a,b) ((a) >= (b) ? (a) : (b))
double genbet(double aa,double bb)
/*
**********************************************************************
double genbet(double aa,double bb)
GeNerate BETa random deviate
Function
Returns a single random deviate from the beta distribution with
parameters A and B. The density of the beta is
x^(a-1) * (1-x)^(b-1) / B(a,b) for 0 < x < 1
Arguments
aa --> First parameter of the beta distribution
bb --> Second parameter of the beta distribution
Method
R. C. H. Cheng
Generating Beta Variatew with Nonintegral Shape Parameters
Communications of the ACM, 21:317-322 (1978)
(Algorithms BB and BC)
**********************************************************************
*/
{
#define expmax 89.0
#define infnty 1.0E38
static double olda = -1.0;
static double oldb = -1.0;
static double genbet,a,alpha,b,beta,delta,gamma,k1,k2,r,s,t,u1,u2,v,w,y,z;
static long qsame;
qsame = olda == aa && oldb == bb;
if (qsame) goto S20;
if (!(aa <= 0.0 || bb <= 0.0)) goto S10;
fputs(" AA or BB <= 0 in GENBET - Abort!",stderr);
fprintf(stderr," AA: %16.6E BB %16.6E\n",aa,bb);
exit(1);
S10:
olda = aa;
oldb = bb;
S20:
if (!(minRnd(aa,bb) > 1.0)) goto S100;
/*
Alborithm BB
Initialize
*/
if (qsame) goto S30;
a = minRnd(aa,bb);
b = maxRnd(aa,bb);
alpha = a+b;
beta = sqrt((alpha-2.0)/(2.0*a*b-alpha));
gamma = a+1.0/beta;
S30:
S40:
u1 = randgen.randDblExc();
/*
Step 1
*/
u2 = randgen.randDblExc();
v = beta*log(u1/(1.0-u1));
if (!(v > expmax)) goto S50;
w = infnty;
goto S60;
S50:
w = a*exp(v);
S60:
z = pow(u1,2.0)*u2;
r = gamma*v-1.3862944;
s = a+r-w;
/*
Step 2
*/
if (s+2.609438 >= 5.0*z) goto S70;
/*
Step 3
*/
t = log(z);
if (s > t) goto S70;
/*
Step 4
*/
if (r+alpha*log(alpha/(b+w)) < t) goto S40;
S70:
/*
Step 5
*/
if (!(aa == a
)) goto S80;
genbet = w/(b+w);
goto S90;
S80:
genbet = b/(b+w);
S90:
goto S230;
S100:
/*
Algorithm BC
Initialize
*/
if (qsame) goto S110;
a = maxRnd(aa,bb);
b = minRnd(aa,bb);
alpha = a+b;
beta = 1.0/b;
delta = 1.0+a-b;
k1 = delta*(1.38889E-2+4.16667E-2*b)/(a*beta-0.777778);
k2 = 0.25+(0.5+0.25/delta)*b;
S110:
S120:
u1 = randgen.randDblExc();
/*
Step 1
*/
u2 = randgen.randDblExc();
if (u1 >= 0.5) goto S130;
/*
Step 2
*/
y = u1*u2;
z = u1*y;
if (0.25*u2+z-y >= k1) goto S120;
goto S170;
S130:
/*
Step 3
*/
z = pow(u1,2.0)*u2;
if (!(z <= 0.25)) goto S160;
v = beta*log(u1/(1.0-u1));
if (!(v > expmax)) goto S140;
w = infnty;
goto S150;
S140:
w = a*exp(v);
S150:
goto S200;
S160:
if (z >= k2) goto S120;
S170:
/*
Step 4
Step 5
*/
v = beta*log(u1/(1.0-u1));
if (!(v > expmax)) goto S180;
w = infnty;
goto S190;
S180:
w = a*exp(v);
S190:
if (alpha*(log(alpha/(b+w))+v)-1.3862944 < log(z)) goto S120;
S200:
/*
Step 6
*/
if (!(a == aa)) goto S210;
genbet = w/(b+w);
goto S220;
S210:
genbet = b/(b+w);
S230:
S220:
return genbet;
#undef expmax
#undef infnty
}