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+/* cdf/hypergeometric.c
+ *
+ * Copyright (C) 2004 Jason H. Stover.
+ *
+ * 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 2 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., 59 Temple Place, Suite 330, Boston, MA 02111-1307, USA.
+ */
+
+/*
+ * Computes the cumulative distribution function for a hypergeometric
+ * random variable. A hypergeometric random variable X is the number
+ * of elements of type 1 in a sample of size t, drawn from a population
+ * of size n1 + n2, in which n1 are of type 1 and n2 are of type 2.
+ *
+ * This algorithm computes Pr( X <= k ) by summing the terms from
+ * the mass function, Pr( X = k ).
+ *
+ * References:
+ *
+ * T. Wu. An accurate computation of the hypergeometric distribution
+ * function. ACM Transactions on Mathematical Software. Volume 19, number 1,
+ * March 1993.
+ * This algorithm is not used, since it requires factoring the
+ * numerator and denominator, then cancelling. It is more accurate
+ * than the algorithm used here, but the cancellation requires more
+ * time than the algorithm used here.
+ *
+ * W. Feller. An Introduction to Probability Theory and Its Applications,
+ * third edition. 1968. Chapter 2, section 6.
+ */
+
+#include <config.h>
+#include <math.h>
+#include <gsl/gsl_math.h>
+#include <gsl/gsl_errno.h>
+#include <gsl/gsl_cdf.h>
+#include <gsl/gsl_randist.h>
+
+#include "error.h"
+
+static double
+lower_tail (const unsigned int k, const unsigned int n1,
+ const unsigned int n2, const unsigned int t)
+{
+ double relerr;
+ int i = k;
+ double s, P;
+
+ s = gsl_ran_hypergeometric_pdf (i, n1, n2, t);
+ P = s;
+
+ while (i > 0)
+ {
+ double factor =
+ (i / (n1 - i + 1.0)) * ((n2 + i - t) / (t - i + 1.0));
+ s *= factor;
+ P += s;
+ relerr = s / P;
+ if (relerr < GSL_DBL_EPSILON)
+ break;
+ i--;
+ }
+
+ return P;
+}
+
+static double
+upper_tail (const unsigned int k, const unsigned int n1,
+ const unsigned int n2, const unsigned int t)
+{
+ double relerr;
+ unsigned int i = k + 1;
+ double s, Q;
+
+ s = gsl_ran_hypergeometric_pdf (i, n1, n2, t);
+ Q = s;
+
+ while (i < t)
+ {
+ double factor =
+ ((n1 - i) / (i + 1.0)) * ((t - i) / (n2 + i + 1.0 - t));
+ s *= factor;
+ Q += s;
+ relerr = s / Q;
+ if (relerr < GSL_DBL_EPSILON)
+ break;
+ i++;
+ }
+
+ return Q;
+}
+
+
+
+
+/*
+ * Pr (X <= k)
+ */
+double
+gsl_cdf_hypergeometric_P (const unsigned int k,
+ const unsigned int n1,
+ const unsigned int n2, const unsigned int t)
+{
+ double P;
+
+ if (t > (n1 + n2))
+ {
+ CDF_ERROR ("t larger than population size", GSL_EDOM);
+ }
+ else if (k >= n1 || k >= t)
+ {
+ P = 1.0;
+ }
+ else if (k < 0.0)
+ {
+ P = 0.0;
+ }
+ else
+ {
+ double midpoint = (int) (t * n1 / (n1 + n2));
+
+ if (k >= midpoint)
+ {
+ P = 1 - upper_tail (k, n1, n2, t);
+ }
+ else
+ {
+ P = lower_tail (k, n1, n2, t);
+ }
+ }
+
+ return P;
+}
+
+/*
+ * Pr (X > k)
+ */
+double
+gsl_cdf_hypergeometric_Q (const unsigned int k,
+ const unsigned int n1,
+ const unsigned int n2, const unsigned int t)
+{
+ double Q;
+
+ if (t > (n1 + n2))
+ {
+ CDF_ERROR ("t larger than population size", GSL_EDOM);
+ }
+ else if (k >= n1 || k >= t)
+ {
+ Q = 0.0;
+ }
+ else if (k < 0.0)
+ {
+ Q = 1.0;
+ }
+ else
+ {
+ double midpoint = (int) (t * n1 / (n1 + n2));
+
+ if (k < midpoint)
+ {
+ Q = 1 - lower_tail (k, n1, n2, t);
+ }
+ else
+ {
+ Q = upper_tail (k, n1, n2, t);
+ }
+ }
+
+ return Q;
+}