;;; PLT Scheme Science Collection ;;; random-distributions/poisson.ss ;;; Copyright (c) 2004 M. Douglas Williams ;;; ;;; This library is free software; you can redistribute it and/or ;;; modify it under the terms of the GNU Lesser General Public ;;; License as published by the Free Software Foundation; either ;;; version 2.1 of the License, or (at your option) any later version. ;;; ;;; This library 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 ;;; Lesser General Public License for more details. ;;; ;;; You should have received a copy of the GNU Lesser General Public ;;; License along with this library; if not, write to the Free ;;; Software Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA ;;; 02111-1307 USA. ;;; ;;; ------------------------------------------------------------------- ;;; ;;; This module implements the poisson distribution. It is based on ;;; the Random Number Distributions in the GNU Scientific Library. ;;; ;;; Version Date Description ;;; 1.0.0 09/28/04 Marked as ready for Release 1.0. Added ;;; contracts for functions (Doug Williams) (module poisson mzscheme (require (lib "contract.ss")) (provide/contract (random-poisson (case-> (-> random-source? real? natural-number/c) (-> real? natural-number/c))) (poisson-pdf (-> natural-number/c real? (>=/c 0.0)))) (require "../random-source.ss") (require "../special-functions/gamma.ss") (require "gamma.ss") (require "binomial.ss") ;; random-poisson: random-source x real -> integer ;; random-poisson: real -> integer ;; ;; This function returns a random variate from a poisson distribution ;; with mean mu. (define random-poisson (case-lambda ((r mu) (let/ec exit (let ((k 0)) (let loop () (if (> mu 10.0) (let* ((m (inexact->exact (truncate (* mu (/ 7.0 8.0))))) (x (random-gamma-int r m))) (if (>= x mu) (exit (+ k (random-binomial r (/ mu x) (- m 1)))) (begin (set! k (+ k m)) (set! mu (- mu x)) (loop)))))) ;; This following method works well when mu is small (let ((emu (exp (- mu))) (prod 1.0)) (let loop () (set! prod (* prod (random-uniform r))) (set! k (+ k 1)) (if (> prod emu) (loop))) (- k 1))))) ((mu) (random-poisson (current-random-source) mu)))) ;; poisson-pdf: integer -> real ;; ;; This function computes the probability density p(x) at x for a ;; poisson distribution with mean mu. (define (poisson-pdf k mu) (let ((lf (lnfact k))) (exp (- (* (log mu) k) lf mu)))) )