80 lines
2.2 KiB
C
80 lines
2.2 KiB
C
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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2020 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "stdlib/stats/base/snanvariancewd.h"
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#include <stdint.h>
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/**
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* Computes the variance of a single-precision floating-point strided array ignoring `NaN` values and using Welford's algorithm.
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*
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* ## References
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*
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* - Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022](https://doi.org/10.1080/00401706.1962.10490022).
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* - van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961](https://doi.org/10.1145/362929.362961).
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*
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* @param N number of indexed elements
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* @param correction degrees of freedom adjustment
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* @param X input array
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* @param stride stride length
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* @return output value
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*/
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float stdlib_strided_snanvariancewd( const int64_t N, const float correction, const float *X, const int64_t stride ) {
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float delta;
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int64_t ix;
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int64_t i;
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double nc;
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double n;
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float M2;
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float mu;
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float v;
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if ( N <= 0 ) {
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return 0.0f / 0.0f; // NaN
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}
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if ( N == 1 || stride == 0 ) {
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v = X[ 0 ];
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if ( v == v && (double)N-(double)correction > 0.0 ) {
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return 0.0f;
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}
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return 0.0f / 0.0f; // NaN
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}
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if ( stride < 0 ) {
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ix = (1-N) * stride;
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} else {
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ix = 0;
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}
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M2 = 0.0f;
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mu = 0.0f;
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n = 0.0;
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for ( i = 0; i < N; i++ ) {
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v = X[ ix ];
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if ( v == v ) {
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delta = v - mu;
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n += 1.0;
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mu += (float)( (double)delta / n );
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M2 += delta * ( v - mu );
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}
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ix += stride;
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}
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nc = n - (double)correction;
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if ( nc <= 0.0 ) {
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return 0.0f / 0.0f; // NaN
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}
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return (double)M2 / nc;
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}
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