uclibc-ng/libm/double/nbdtr.c

/*							nbdtr.c
 *
 *	Negative binomial distribution
 *
 *
 *
 * SYNOPSIS:
 *
 * int k, n;
 * double p, y, nbdtr();
 *
 * y = nbdtr( k, n, p );
 *
 * DESCRIPTION:
 *
 * Returns the sum of the terms 0 through k of the negative
 * binomial distribution:
 *
 *   k
 *   --  ( n+j-1 )   n      j
 *   >   (       )  p  (1-p)
 *   --  (   j   )
 *  j=0
 *
 * In a sequence of Bernoulli trials, this is the probability
 * that k or fewer failures precede the nth success.
 *
 * The terms are not computed individually; instead the incomplete
 * beta integral is employed, according to the formula
 *
 * y = nbdtr( k, n, p ) = incbet( n, k+1, p ).
 *
 * The arguments must be positive, with p ranging from 0 to 1.
 *
 * ACCURACY:
 *
 * Tested at random points (a,b,p), with p between 0 and 1.
 *
 *               a,b                     Relative error:
 * arithmetic  domain     # trials      peak         rms
 *    IEEE     0,100       100000      1.7e-13     8.8e-15
 * See also incbet.c.
 *
 */
/*							nbdtrc.c
 *
 *	Complemented negative binomial distribution
 *
 *
 *
 * SYNOPSIS:
 *
 * int k, n;
 * double p, y, nbdtrc();
 *
 * y = nbdtrc( k, n, p );
 *
 * DESCRIPTION:
 *
 * Returns the sum of the terms k+1 to infinity of the negative
 * binomial distribution:
 *
 *   inf
 *   --  ( n+j-1 )   n      j
 *   >   (       )  p  (1-p)
 *   --  (   j   )
 *  j=k+1
 *
 * The terms are not computed individually; instead the incomplete
 * beta integral is employed, according to the formula
 *
 * y = nbdtrc( k, n, p ) = incbet( k+1, n, 1-p ).
 *
 * The arguments must be positive, with p ranging from 0 to 1.
 *
 * ACCURACY:
 *
 * Tested at random points (a,b,p), with p between 0 and 1.
 *
 *               a,b                     Relative error:
 * arithmetic  domain     # trials      peak         rms
 *    IEEE     0,100       100000      1.7e-13     8.8e-15
 * See also incbet.c.
 */

/*							nbdtrc
 *
 *	Complemented negative binomial distribution
 *
 *
 *
 * SYNOPSIS:
 *
 * int k, n;
 * double p, y, nbdtrc();
 *
 * y = nbdtrc( k, n, p );
 *
 * DESCRIPTION:
 *
 * Returns the sum of the terms k+1 to infinity of the negative
 * binomial distribution:
 *
 *   inf
 *   --  ( n+j-1 )   n      j
 *   >   (       )  p  (1-p)
 *   --  (   j   )
 *  j=k+1
 *
 * The terms are not computed individually; instead the incomplete
 * beta integral is employed, according to the formula
 *
 * y = nbdtrc( k, n, p ) = incbet( k+1, n, 1-p ).
 *
 * The arguments must be positive, with p ranging from 0 to 1.
 *
 * ACCURACY:
 *
 * See incbet.c.
 */
/*							nbdtri
 *
 *	Functional inverse of negative binomial distribution
 *
 *
 *
 * SYNOPSIS:
 *
 * int k, n;
 * double p, y, nbdtri();
 *
 * p = nbdtri( k, n, y );
 *
 * DESCRIPTION:
 *
 * Finds the argument p such that nbdtr(k,n,p) is equal to y.
 *
 * ACCURACY:
 *
 * Tested at random points (a,b,y), with y between 0 and 1.
 *
 *               a,b                     Relative error:
 * arithmetic  domain     # trials      peak         rms
 *    IEEE     0,100       100000      1.5e-14     8.5e-16
 * See also incbi.c.
 */

/*
Cephes Math Library Release 2.8:  June, 2000
Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
*/

#include <math.h>
#ifdef ANSIPROT
extern double incbet ( double, double, double );
extern double incbi ( double, double, double );
#else
double incbet(), incbi();
#endif

double nbdtrc( k, n, p )
int k, n;
double p;
{
double dk, dn;

if( (p < 0.0) || (p > 1.0) )
	goto domerr;
if( k < 0 )
	{
domerr:
	mtherr( "nbdtr", DOMAIN );
	return( 0.0 );
	}

dk = k+1;
dn = n;
return( incbet( dk, dn, 1.0 - p ) );
}



double nbdtr( k, n, p )
int k, n;
double p;
{
double dk, dn;

if( (p < 0.0) || (p > 1.0) )
	goto domerr;
if( k < 0 )
	{
domerr:
	mtherr( "nbdtr", DOMAIN );
	return( 0.0 );
	}
dk = k+1;
dn = n;
return( incbet( dn, dk, p ) );
}



double nbdtri( k, n, p )
int k, n;
double p;
{
double dk, dn, w;

if( (p < 0.0) || (p > 1.0) )
	goto domerr;
if( k < 0 )
	{
domerr:
	mtherr( "nbdtri", DOMAIN );
	return( 0.0 );
	}
dk = k+1;
dn = n;
w = incbi( dn, dk, p );
return( w );
}