gsl_randist__lognormal.c 1.9 KB

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  1. /* randist/lognormal.c
  2. *
  3. * Copyright (C) 1996, 1997, 1998, 1999, 2000, 2007 James Theiler, Brian Gough
  4. *
  5. * This program is free software; you can redistribute it and/or modify
  6. * it under the terms of the GNU General Public License as published by
  7. * the Free Software Foundation; either version 3 of the License, or (at
  8. * your option) any later version.
  9. *
  10. * This program is distributed in the hope that it will be useful, but
  11. * WITHOUT ANY WARRANTY; without even the implied warranty of
  12. * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
  13. * General Public License for more details.
  14. *
  15. * You should have received a copy of the GNU General Public License
  16. * along with this program; if not, write to the Free Software
  17. * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
  18. */
  19. #include "gsl__config.h"
  20. #include <math.h>
  21. #include "gsl_math.h"
  22. #include "gsl_rng.h"
  23. #include "gsl_randist.h"
  24. /* The lognormal distribution has the form
  25. p(x) dx = 1/(x * sqrt(2 pi sigma^2)) exp(-(ln(x) - zeta)^2/2 sigma^2) dx
  26. for x > 0. Lognormal random numbers are the exponentials of
  27. gaussian random numbers */
  28. double
  29. gsl_ran_lognormal (const gsl_rng * r, const double zeta, const double sigma)
  30. {
  31. double u, v, r2, normal, z;
  32. do
  33. {
  34. /* choose x,y in uniform square (-1,-1) to (+1,+1) */
  35. u = -1 + 2 * gsl_rng_uniform (r);
  36. v = -1 + 2 * gsl_rng_uniform (r);
  37. /* see if it is in the unit circle */
  38. r2 = u * u + v * v;
  39. }
  40. while (r2 > 1.0 || r2 == 0);
  41. normal = u * sqrt (-2.0 * log (r2) / r2);
  42. z = exp (sigma * normal + zeta);
  43. return z;
  44. }
  45. double
  46. gsl_ran_lognormal_pdf (const double x, const double zeta, const double sigma)
  47. {
  48. if (x <= 0)
  49. {
  50. return 0 ;
  51. }
  52. else
  53. {
  54. double u = (log (x) - zeta)/sigma;
  55. double p = 1 / (x * fabs(sigma) * sqrt (2 * M_PI)) * exp (-(u * u) /2);
  56. return p;
  57. }
  58. }