📄 nbdtr.c
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/* 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, 2000Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier*/#include <math.h>#ifdef ANSIPROTextern double incbet ( double, double, double );extern double incbi ( double, double, double );#elsedouble incbet(), incbi();#endifdouble 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 );}
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