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- // This may look like C code, but it is really -*- C++ -*-
- /*
- Copyright (C) 1988 Free Software Foundation
- written by Dirk Grunwald (grunwald@cs.uiuc.edu)
-
- This file is part of GNU CC.
-
- GNU CC is distributed in the hope that it will be useful,
- but WITHOUT ANY WARRANTY. No author or distributor
- accepts responsibility to anyone for the consequences of using it
- or for whether it serves any particular purpose or works at all,
- unless he says so in writing. Refer to the GNU CC General Public
- License for full details.
-
- Everyone is granted permission to copy, modify and redistribute
- GNU CC, but only under the conditions described in the
- GNU CC General Public License. A copy of this license is
- supposed to have been given to you along with GNU CC so you
- can know your rights and responsibilities. It should be in a
- file named COPYING. Among other things, the copyright notice
- and this notice must be preserved on all copies.
- */
- #include <stream.h>
- #include "SampleStatistic.h"
- #include <math.h>
-
- // error handling
-
- void default_SampleStatistic_error_handler(char* msg)
- {
- cerr << "Fatal SampleStatistic error. " << msg << "\n";
- exit(1);
- }
-
- //one_arg_error_handler_t SampleStatistic_error_handler = default_SampleStatistic_error_handler;
-
- // one_arg_error_handler_t set_SampleStatistic_error_handler(one_arg_error_handler_t f)
- // {
- // one_arg_error_handler_t old = SampleStatistic_error_handler;
- // SampleStatistic_error_handler = f;
- // return old;
- // }
- //
-
- void SampleStatistic::error(char* msg)
- {
- // (*SampleStatistic_error_handler)(msg);
- default_SampleStatistic_error_handler(msg);
- }
-
- void
- SampleStatistic::reset()
- {
- n = 0; x = x2 = 0.0;
- maxValue = -MAXFLOAT;
- minValue = MAXFLOAT;
- }
-
- void
- SampleStatistic::operator+=(double value)
- {
- n ++;
- x += value;
- x2 += (value * value);
- if ( minValue > value) minValue = value;
- if ( maxValue < value) maxValue = value;
- }
-
- double
- SampleStatistic::mean()
- {
- if ( n > 0) {
- return (x / n);
- }
- else {
- return ( 0.0 );
- }
- }
-
- double
- SampleStatistic::var()
- {
- if ( n > 1) {
- return(( x2 - ((x * x) / n)) / ( n - 1));
- }
- else {
- return ( 0.0 );
- }
- }
-
- double
- SampleStatistic::stdDev()
- {
- if ( n <= 0 || this -> var() <= 0) {
- return(0);
- } else {
- return( (double) sqrt( var() ) );
- }
- }
-
- int
- SampleStatistic::samples()
- {
- return(n);
- }
-
- double
- SampleStatistic::min()
- {
- return(minValue);
- }
-
- double
- SampleStatistic::max()
- {
- return(maxValue);
- }
-
- double
- SampleStatistic::sum()
- {
- return(x);
- }
-
- // t-distribution: given p-value and degrees of freedom, return t-value
- // adapted from Peizer & Pratt JASA, vol63, p1416
-
- double
- SampleStatistic::tval(double p, int df)
- {
- double t;
- int positive = p >= 0.5;
- p = (positive)? 1.0 - p : p;
- if (p <= 0.0 || df == 0)
- t = HUGE;
- else if (p == 0.5)
- t = 0.0;
- else if (df == 1)
- t = 1.0 / tan((p + p) * 1.57079633);
- else if (df == 2)
- t = sqrt(1.0 / ((p + p) * (1.0 - p)) - 2.0);
- else
- {
- double ddf = df;
- double a = sqrt(log(1.0 / (p * p)));
- double aa = a * a;
- a = a - ((2.515517 + (0.802853 * a) + (0.010328 * aa)) /
- (1.0 + (1.432788 * a) + (0.189269 * aa) +
- (0.001308 * aa * a)));
- t = ddf - 0.666666667 + 1.0 / (10.0 * ddf);
- t = sqrt(ddf * (exp(a * a * (ddf - 0.833333333) / (t * t)) - 1.0));
- }
- return (positive)? t : -t;
- }
-
- double
- SampleStatistic::confidence(int interval)
- {
- int samp = samples() - 1;
- double t = tval(double(100 + interval) * 0.005, samp );
-
- if (t == HUGE)
- return t;
- else
- return (t * stdDev()) / sqrt(double( samp ));
- }
-
- double
- SampleStatistic::confidence(double p_value)
- {
- int samp = samples() - 1;
- double t = tval((1.0 + p_value) * 0.5, samp);
- if (t == HUGE)
- return t;
- else
- return (t * stdDev()) / sqrt(double( samp ));
- }
-