/* cdf/gammainv.c * * Copyright (C) 2003, 2007 Brian Gough * * 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, write to the Free Software Foundation, * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. */ #include #include #include #include #include #include #include double gsl_cdf_gamma_Pinv (const double P, const double a, const double b) { double x; if (P == 1.0) { return GSL_POSINF; } else if (P == 0.0) { return 0.0; } /* Consider, small, large and intermediate cases separately. The boundaries at 0.05 and 0.95 have not been optimised, but seem ok for an initial approximation. BJG: These approximations aren't really valid, the relevant criterion is P*gamma(a+1) < 1. Need to rework these routines and use a single bisection style solver for all the inverse functions. */ if (P < 0.05) { double x0 = exp ((gsl_sf_lngamma (a) + log (P)) / a); x = x0; } else if (P > 0.95) { double x0 = -log1p (-P) + gsl_sf_lngamma (a); x = x0; } else { double xg = gsl_cdf_ugaussian_Pinv (P); double x0 = (xg < -0.5*sqrt (a)) ? a : sqrt (a) * xg + a; x = x0; } /* Use Lagrange's interpolation for E(x)/phi(x0) to work backwards to an improved value of x (Abramowitz & Stegun, 3.6.6) where E(x)=P-integ(phi(u),u,x0,x) and phi(u) is the pdf. */ { double lambda, dP, phi; unsigned int n = 0; start: dP = P - gsl_cdf_gamma_P (x, a, 1.0); phi = gsl_ran_gamma_pdf (x, a, 1.0); // printf("%12.5f, %12.5f, %12.5f, %12.5f\n", x, a, dP, phi); if (dP == 0.0 || n++ > 100) goto end; lambda = dP / GSL_MAX (2 * fabs (dP / x), phi); { double step0 = lambda; double step1 = -((a - 1) / x - 1) * lambda * lambda / 4.0; double step = step0; if (fabs (step1) < 0.5 * fabs (step0)) step += step1; if (x + step > 0) x += step; else { x /= 2.0; } if (fabs (step0) > 1e-10 * x || fabs(step0 * phi) > 1e-10 * P) goto start; } end: /* Follow IMSL and say after 100 iterations we'll call the present * result good. if (fabs(dP) > GSL_SQRT_DBL_EPSILON * P) { GSL_ERROR_VAL("inverse failed to converge", GSL_EFAILED, GSL_NAN); } */ return b * x; } } double gsl_cdf_gamma_Qinv (const double Q, const double a, const double b) { double x; if (Q == 1.0) { return 0.0; } else if (Q == 0.0) { return GSL_POSINF; } /* Consider, small, large and intermediate cases separately. The boundaries at 0.05 and 0.95 have not been optimised, but seem ok for an initial approximation. */ if (Q < 0.05) { double x0 = -log (Q) + gsl_sf_lngamma (a); x = x0; } else if (Q > 0.95) { double x0 = exp ((gsl_sf_lngamma (a) + log1p (-Q)) / a); x = x0; } else { double xg = gsl_cdf_ugaussian_Qinv (Q); double x0 = (xg < -0.5*sqrt (a)) ? a : sqrt (a) * xg + a; x = x0; } /* Use Lagrange's interpolation for E(x)/phi(x0) to work backwards to an improved value of x (Abramowitz & Stegun, 3.6.6) where E(x)=P-integ(phi(u),u,x0,x) and phi(u) is the pdf. */ { double lambda, dQ, phi; unsigned int n = 0; start: dQ = Q - gsl_cdf_gamma_Q (x, a, 1.0); phi = gsl_ran_gamma_pdf (x, a, 1.0); if (dQ == 0.0 || n++ > 32) goto end; lambda = -dQ / GSL_MAX (2 * fabs (dQ / x), phi); { double step0 = lambda; double step1 = -((a - 1) / x - 1) * lambda * lambda / 4.0; double step = step0; if (fabs (step1) < 0.5 * fabs (step0)) step += step1; if (x + step > 0) x += step; else { x /= 2.0; } if (fabs (step0) > 1e-10 * x) goto start; } } end: return b * x; }