X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;f=lib%2Ftukey%2Fqtukey.c;fp=lib%2Ftukey%2Fqtukey.c;h=08253df7546b4bb051cedc0e957b3215512e1d14;hb=631e2243322503338b497cd13529fbb2c5833e3d;hp=0000000000000000000000000000000000000000;hpb=16a331300d4c9deb96c3ca34cd1f470c762c8fad;p=pspp
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+/* PSPP - a program for statistical analysis.
+ Copyright (C) 2011 Free Software Foundation, Inc.
+
+ 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, see .
+*/
+
+/* This file is taken from the R project source code, and modified.
+ The original copyright notice is reproduced below: */
+
+/*
+ * Mathlib : A C Library of Special Functions
+ * Copyright (C) 1998 Ross Ihaka
+ * Copyright (C) 2000--2005 The R Development Core Team
+ * based in part on AS70 (C) 1974 Royal Statistical Society
+ *
+ * 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, a copy is available at
+ * http://www.r-project.org/Licenses/
+ *
+ * SYNOPSIS
+ *
+ * #include
+ * double qtukey(p, rr, cc, df, lower_tail, log_p);
+ *
+ * DESCRIPTION
+ *
+ * Computes the quantiles of the maximum of rr studentized
+ * ranges, each based on cc means and with df degrees of freedom
+ * for the standard error, is less than q.
+ *
+ * The algorithm is based on that of the reference.
+ *
+ * REFERENCE
+ *
+ * Copenhaver, Margaret Diponzio & Holland, Burt S.
+ * Multiple comparisons of simple effects in
+ * the two-way analysis of variance with fixed effects.
+ * Journal of Statistical Computation and Simulation,
+ * Vol.30, pp.1-15, 1988.
+ */
+
+#include
+
+#include "tukey.h"
+
+#include
+#include
+
+#define TRUE (1)
+#define FALSE (0)
+
+#define ML_POSINF (1.0 / 0.0)
+#define ML_NEGINF (-1.0 / 0.0)
+
+#define R_D_Lval(p) (lower_tail ? (p) : (0.5 - (p) + 0.5)) /* p */
+
+#define R_DT_qIv(p) (log_p ? (lower_tail ? exp(p) : - expm1(p)) \
+ : R_D_Lval(p))
+
+
+static double fmax2(double x, double y)
+{
+#ifdef IEEE_754
+ if (ISNAN(x) || ISNAN(y))
+ return x + y;
+#endif
+ return (x < y) ? y : x;
+}
+
+
+#define R_Q_P01_boundaries(p, _LEFT_, _RIGHT_) \
+ if (log_p) { \
+ assert (p <= 0); \
+ if(p == 0) /* upper bound*/ \
+ return lower_tail ? _RIGHT_ : _LEFT_; \
+ if(p == ML_NEGINF) \
+ return lower_tail ? _LEFT_ : _RIGHT_; \
+ } \
+ else { /* !log_p */ \
+ assert (p >= 0 && p <= 1); \
+ if(p == 0) \
+ return lower_tail ? _LEFT_ : _RIGHT_; \
+ if(p == 1) \
+ return lower_tail ? _RIGHT_ : _LEFT_; \
+ }
+
+
+/* qinv() :
+ * this function finds percentage point of the studentized range
+ * which is used as initial estimate for the secant method.
+ * function is adapted from portion of algorithm as 70
+ * from applied statistics (1974) ,vol. 23, no. 1
+ * by odeh, r. e. and evans, j. o.
+ *
+ * p = percentage point
+ * c = no. of columns or treatments
+ * v = degrees of freedom
+ * qinv = returned initial estimate
+ *
+ * vmax is cutoff above which degrees of freedom
+ * is treated as infinity.
+ */
+
+static double qinv(double p, double c, double v)
+{
+ static const double p0 = 0.322232421088;
+ static const double q0 = 0.993484626060e-01;
+ static const double p1 = -1.0;
+ static const double q1 = 0.588581570495;
+ static const double p2 = -0.342242088547;
+ static const double q2 = 0.531103462366;
+ static const double p3 = -0.204231210125;
+ static const double q3 = 0.103537752850;
+ static const double p4 = -0.453642210148e-04;
+ static const double q4 = 0.38560700634e-02;
+ static const double c1 = 0.8832;
+ static const double c2 = 0.2368;
+ static const double c3 = 1.214;
+ static const double c4 = 1.208;
+ static const double c5 = 1.4142;
+ static const double vmax = 120.0;
+
+ double ps, q, t, yi;
+
+ ps = 0.5 - 0.5 * p;
+ yi = sqrt (log (1.0 / (ps * ps)));
+ t = yi + (((( yi * p4 + p3) * yi + p2) * yi + p1) * yi + p0)
+ / (((( yi * q4 + q3) * yi + q2) * yi + q1) * yi + q0);
+ if (v < vmax) t += (t * t * t + t) / v / 4.0;
+ q = c1 - c2 * t;
+ if (v < vmax) q += -c3 / v + c4 * t / v;
+ return t * (q * log (c - 1.0) + c5);
+}
+
+/*
+ * Copenhaver, Margaret Diponzio & Holland, Burt S.
+ * Multiple comparisons of simple effects in
+ * the two-way analysis of variance with fixed effects.
+ * Journal of Statistical Computation and Simulation,
+ * Vol.30, pp.1-15, 1988.
+ *
+ * Uses the secant method to find critical values.
+ *
+ * p = confidence level (1 - alpha)
+ * rr = no. of rows or groups
+ * cc = no. of columns or treatments
+ * df = degrees of freedom of error term
+ *
+ * ir(1) = error flag = 1 if wprob probability > 1
+ * ir(2) = error flag = 1 if ptukey probability > 1
+ * ir(3) = error flag = 1 if convergence not reached in 50 iterations
+ * = 2 if df < 2
+ *
+ * qtukey = returned critical value
+ *
+ * If the difference between successive iterates is less than eps,
+ * the search is terminated
+ */
+
+
+double qtukey(double p, double rr, double cc, double df,
+ int lower_tail, int log_p)
+{
+ static const double eps = 0.0001;
+ const int maxiter = 50;
+
+ double ans = 0.0, valx0, valx1, x0, x1, xabs;
+ int iter;
+
+#ifdef IEEE_754
+ if (ISNAN(p) || ISNAN(rr) || ISNAN(cc) || ISNAN(df)) {
+ ML_ERROR(ME_DOMAIN, "qtukey");
+ return p + rr + cc + df;
+ }
+#endif
+
+ /* df must be > 1 ; there must be at least two values */
+ assert (! (df < 2 || rr < 1 || cc < 2) );
+
+ R_Q_P01_boundaries (p, 0, ML_POSINF);
+
+ p = R_DT_qIv(p); /* lower_tail,non-log "p" */
+
+ /* Initial value */
+
+ x0 = qinv(p, cc, df);
+
+ /* Find prob(value < x0) */
+
+ valx0 = ptukey(x0, rr, cc, df, /*LOWER*/TRUE, /*LOG_P*/FALSE) - p;
+
+ /* Find the second iterate and prob(value < x1). */
+ /* If the first iterate has probability value */
+ /* exceeding p then second iterate is 1 less than */
+ /* first iterate; otherwise it is 1 greater. */
+
+ if (valx0 > 0.0)
+ x1 = fmax2(0.0, x0 - 1.0);
+ else
+ x1 = x0 + 1.0;
+ valx1 = ptukey(x1, rr, cc, df, /*LOWER*/TRUE, /*LOG_P*/FALSE) - p;
+
+ /* Find new iterate */
+
+ for(iter=1 ; iter < maxiter ; iter++) {
+ ans = x1 - ((valx1 * (x1 - x0)) / (valx1 - valx0));
+ valx0 = valx1;
+
+ /* New iterate must be >= 0 */
+
+ x0 = x1;
+ if (ans < 0.0) {
+ ans = 0.0;
+ valx1 = -p;
+ }
+ /* Find prob(value < new iterate) */
+
+ valx1 = ptukey(ans, rr, cc, df, /*LOWER*/TRUE, /*LOG_P*/FALSE) - p;
+ x1 = ans;
+
+ /* If the difference between two successive */
+ /* iterates is less than eps, stop */
+
+ xabs = fabs(x1 - x0);
+ if (xabs < eps)
+ return ans;
+ }
+
+ /* The process did not converge in 'maxiter' iterations */
+ assert (0);
+ return ans;
+}