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size_t gsl_stats_max_index ( const double data, size_t stride, size_t n ) ¶ This function finds both the minimum and maximum values min, void gsl_stats_minmax ( double * min, double * max, const double data, size_t stride, size_t n ) ¶ If you want instead to find the element with the smallest absoluteīefore calling this function. This function returns the minimum value in data, a dataset of double gsl_stats_min ( const double data, size_t stride, size_t n ) ¶
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Magnitude you will need to apply fabs() or abs() to your dataīefore calling this function. If you want instead to find the element with the largest absolute The maximum value is definedĪs the value of the element which satisfies This function returns the maximum value in data, a dataset of double gsl_stats_max ( const double data, size_t stride, size_t n ) ¶ For functions which return an index, the location of theįirst NaN in the array is returned. NaN will be returned, since the maximum or minimum value is The following functions find the maximum and minimum values of aĭataset (or their indices). The variance replaces the sample mean by the known
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This function computes an unbiased estimate of the variance of the weightedĭataset data when the population mean mean of the underlyingĭistribution is known a priori. double gsl_stats_wvariance_with_fixed_mean ( const double w, size_t wstride, const double data, size_t stride, size_t n, const double mean ) ¶ double gsl_stats_wsd_m ( const double w, size_t wstride, const double data, size_t stride, size_t n, double wmean ) ¶įunction gsl_stats_wvariance_m() above. This function returns the square root of the corresponding varianceįunction gsl_stats_wvariance() above. The standard deviation is defined as the square root of the variance. double gsl_stats_wsd ( const double w, size_t wstride, const double data, size_t stride, size_t n ) ¶ This function returns the estimated variance of the weighted datasetĭata using the given weighted mean wmean. double gsl_stats_wvariance_m ( const double w, size_t wstride, const double data, size_t stride, size_t n, double wmean ) ¶ Note that this expression reduces to an unweighted variance with theįamiliar factor when there are equal non-zero