wkurtosis_source.c

该文件为c++的数学函数库!是一个非常有用的编程工具.它含有各种数学函数,为科学计算、工程应用等程序编写提供方便！

/* statistics/wkurtosis_source.c
 * 
 * Copyright (C) 1996, 1997, 1998, 1999, 2000 Jim Davies, Brian Gough
 * 
 * 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., 675 Mass Ave, Cambridge, MA 02139, USA.
 */

double 
FUNCTION(gsl_stats,wkurtosis) (const BASE w[], const size_t wstride, const BASE data[], const size_t stride, const size_t n)
{
  const double wmean = FUNCTION(gsl_stats,wmean)(w, wstride, data, stride, n);
  const double wsd = FUNCTION(gsl_stats,wsd_m)(w, wstride, data, stride, n, wmean);
  return FUNCTION(gsl_stats,wkurtosis_m_sd)(w, wstride, data, stride, n, wmean, wsd);
}
    
double 
FUNCTION(gsl_stats,wkurtosis_m_sd) (const BASE w[], const size_t wstride,
                                    const BASE data[], 
                                    const size_t stride,
                                    const size_t n,
                                    const double wmean, 
                                    const double wsd)
{
  /* takes a dataset and finds the kurtosis */

  long double wavg = 0, kurtosis;
  long double W = 0;
  size_t i;

  /* find the fourth moment the deviations, normalized by the sd */

  /* we use a recurrence relation to stably update a running value so
     there aren't any large sums that can overflow */

  for (i = 0; i < n; i++)
    {
      BASE wi = w[i * wstride];
      
      if (wi > 0) {
        const long double x = (data[i * stride] - wmean) / wsd;
        W += wi ;
        wavg += (x * x * x * x - wavg) * (wi / W);
      }
    }

  kurtosis = wavg - 3.0;  /* makes kurtosis zero for a Gaussian */

  return kurtosis;
}