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Author: aayush0325

lib/node_modules/@stdlib/stats/base/dmeanvarpn/README.md

@@ -226,6 +226,119 @@ console.log( out );
 
 <!-- /.examples -->
 
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dmeanvarpn.h"
+```
+
+#### stdlib_strided_dmeanvarpn( N, correction, \*X, strideX, \*Out, strideOut )
+
+Computes the [mean][arithmetic-mean] and [variance][variance] of a double-precision floating-point strided array using a two-pass algorithm.
+
+```c
+const double x[] = { 1.0, -2.0, 2.0 };
+double out[] = { 0.0, 0.0 }
+
+stdlib_strided_dmeanvarpn( 3, 1.0, x, 1, out, 1 );
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction).
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **Out**: `[out] double*` output array.
+-   **strideOut**: `[in] CBLAS_INT` stride length for `Out`.
+
+```c
+double stdlib_strided_dmeanvarpn( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, double *Out, const CBLAS_INT strideOut );
+```
+
+#### stdlib_strided_dmeanvarpn( N, correction, \*X, strideX, offsetX, \*Out, strideOut, offsetOut )
+
+Computes the [mean][arithmetic-mean] and [variance][variance] of a double-precision floating-point strided array using a two-pass algorithm and alternative indexing semantics.
+
+```c
+const double x[] = { 1.0, -2.0, 2.0 };
+double out[] = { 0.0, 0.0 }
+
+stdlib_strided_dmeanvarpn_ndarray( 3, 1.0, x, 1, 0, out, 1, 0 );
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction).
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+-   **Out**: `[out] double*` output array.
+-   **strideOut**: `[in] CBLAS_INT` stride length for `Out`.
+-   **offsetOut**: `[in] CBLAS_INT` starting index for `Out`.
+
+```c
+double stdlib_strided_dmeanvarpn_ndarray( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Out, const CBLAS_INT strideOut, const CBLAS_INT offsetOut );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/dmeanvarpn.h"
+#include <stdio.h>
+
+int main( void ) {
+    // Create a strided array:
+    const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 };
+
+    // Create an output array:
+    double out[] = { 0.0, 0.0 };
+
+    // Specify the number of elements:
+    const int N = 4;
+
+    // Specify the stride lengths:
+    const int strideX = 2;
+    const int strideOut = 1;
+
+    // Compute the mean and variance:
+    stdlib_strided_dmeanvarpn( N, 1.0, x, strideX, out, strideOut );
+
+    // Print the result:
+    printf( "sample mean: %lf\n", out[ 0 ] );
+    printf( "sample variance: %lf\n", out[ 1 ] );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 * * *
 
 <section class="references">