time-to-botec/js/node_modules/@stdlib/stats/base/dnanmeanwd/src/dnanmeanwd.c

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/**
* @license Apache-2.0
*
* Copyright (c) 2020 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "stdlib/stats/base/dnanmeanwd.h"
#include <stdint.h>
/**
* Computes the arithmetic mean of a double-precision floating-point strided array, using Welford's algorithm and ignoring `NaN` values.
*
* ## Method
*
* - This implementation uses Welford's algorithm for efficient computation, which can be derived as follows
*
* ```tex
* \begin{align*}
* \mu_n &= \frac{1}{n} \sum_{i=0}^{n-1} x_i \\
* &= \frac{1}{n} \biggl(x_{n-1} + \sum_{i=0}^{n-2} x_i \biggr) \\
* &= \frac{1}{n} (x_{n-1} + (n-1)\mu_{n-1}) \\
* &= \mu_{n-1} + \frac{1}{n} (x_{n-1} - \mu_{n-1})
* \end{align*}
* ```
*
* ## References
*
* - Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 41920. doi:[10.1080/00401706.1962.10490022](https://doi.org/10.1080/00401706.1962.10490022).
* - van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 14950. doi:[10.1145/362929.362961](https://doi.org/10.1145/362929.362961).
*
* @param N number of indexed elements
* @param X input array
* @param stride stride length
* @return output value
*/
double stdlib_strided_dnanmeanwd( const int64_t N, const double *X, const int64_t stride ) {
int64_t ix;
int64_t i;
int64_t n;
double mu;
double v;
if ( N <= 0 ) {
return 0.0 / 0.0; // NaN
}
if ( N == 1 || stride == 0 ) {
return X[ 0 ];
}
if ( stride < 0 ) {
ix = (1-N) * stride;
} else {
ix = 0;
}
mu = 0.0;
n = 0;
for ( i = 0; i < N; i++ ) {
v = X[ ix ];
if ( v == v ) {
n += 1;
mu += ( v-mu ) / (double)n;
}
ix += stride;
}
if ( n == 0 ) {
return 0.0 / 0.0; // NaN;
}
return mu;
}