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feat: add C ndarray interface and refactor implementation for stats/base/dnanvariancech #4803

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Resolves None.

Description

What is the purpose of this pull request?

This pull request:

  • adds C ndarray interface for stats/base/dnanvariancech
  • refactors JavaScript implementation
  • updates tests, docs, examples and benchmarks

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  • resolves None.

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@stdlib-js/reviewers

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@stdlib-bot stdlib-bot added Statistics Issue or pull request related to statistical functionality. Needs Review A pull request which needs code review. labels Jan 18, 2025
@0PrashantYadav0
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@aayush0325 Will you provide a quick review for this one as well. Thank you.

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stdlib-bot commented Jan 18, 2025

Coverage Report

Package Statements Branches Functions Lines
stats/base/dnanvariancech $\color{green}422/422$
$\color{green}+100.00\%$
$\color{green}32/32$
$\color{green}+100.00\%$
$\color{green}4/4$
$\color{green}+100.00\%$
$\color{green}422/422$
$\color{green}+100.00\%$

The above coverage report was generated for the changes in this PR.

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#### stdlib_strided_dnanvariancech( N, correction, \*X, strideX )

Computes the [variance][variance] of a double-precision floating-point strided array `x` ignoring `NaN` values and using a one-pass trial mean algorithm.
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Suggested change
Computes the [variance][variance] of a double-precision floating-point strided array `x` ignoring `NaN` values and using a one-pass trial mean algorithm.
Computes the [variance][variance] of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass trial mean algorithm.

Computes the [variance][variance] of a double-precision floating-point strided array `x` ignoring `NaN` values and using a one-pass trial mean algorithm.

```c
const double x[] = { 1.0, -2.0, 0.0/0.0, 2.0 };
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Suggested change
const double x[] = { 1.0, -2.0, 0.0/0.0, 2.0 };
const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 };

since these values come directly from example.c

```c
const double x[] = { 1.0, -2.0, 0.0/0.0, 2.0 };

double v = stdlib_strided_dnanvariancech( 4, 1.0, x, 1 );
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@Neerajpathak07 Neerajpathak07 Jan 18, 2025

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double v = stdlib_strided_dnanvariancech( 4, 1.0, x, 1 );
double v = stdlib_strided_dnanvariancech( 6, 1.0, x, 2 );

const double x[] = { 1.0, -2.0, 0.0/0.0, 2.0 };

double v = stdlib_strided_dnanvariancech( 4, 1.0, x, 1 );
// returns ~4.3333
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You'll have to compute the return value for the new const x[] array.
You can also take help of repl for finding the value.

Computes the [variance][variance] of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass trial mean algorithm and alternative indexing semantics.

```c
const double x[] = { 1.0, -2.0, 2.0 };
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Same goes for this as well.

double elapsed;
double x[ len ];
double v;
double t;
int i;

for ( i = 0; i < len; i++ ) {
x[ i ] = ( rand_double() * 20000.0 ) - 10000.0;
if ( rand_double() < 0.2 ) {
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not sure if you need to change this.

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@0PrashantYadav0 Hey just a few comments similar to one of your previous PR. Also would you please look for these changes in your other PR's as well.

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