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📄 nbdtr.cpp

📁 非常著名的曲线拟合程序
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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 2.3:  March, 1995Copyright 1984, 1987, 1995 by Stephen L. Moshier*/#include <config.h>#include "mconf.h"#ifndef ANSIPROTdouble incbet(), incbi();#endifdouble nbdtrc( int k, int 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( int k, int 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( int k, int 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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