docs: update namespace table of contents

PR-URL: #7433

Co-authored-by: Philipp Burckhardt <[email protected]>
Reviewed-by: Philipp Burckhardt <[email protected]>
Signed-off-by: stdlib-bot <[email protected]>

Author: stdlib-bot

lib/node_modules/@stdlib/blas/base/README.md

@@ -88,7 +88,7 @@ var o = blas;
 -   <span class="signature">[`zaxpy( N, alpha, x, strideX, y, strideY )`][@stdlib/blas/base/zaxpy]</span><span class="delimiter">: </span><span class="description">scale a double-precision complex floating-point vector by a double-precision complex floating-point constant and add the result to a double-precision complex floating-point vector.</span>
 -   <span class="signature">[`zcopy( N, x, strideX, y, strideY )`][@stdlib/blas/base/zcopy]</span><span class="delimiter">: </span><span class="description">copy values from one complex double-precision floating-point vector to another complex double-precision floating-point vector.</span>
 -   <span class="signature">[`zdrot( N, x, strideX, y, strideY, c, s )`][@stdlib/blas/base/zdrot]</span><span class="delimiter">: </span><span class="description">apply a plane rotation.</span>
--   <span class="signature">[`zdscal( N, da, zx, strideZX )`][@stdlib/blas/base/zdscal]</span><span class="delimiter">: </span><span class="description">scale a double-precision complex floating-point vector by a double-precision floating-point constant.</span>
+-   <span class="signature">[`zdscal( N, alpha, x, strideX )`][@stdlib/blas/base/zdscal]</span><span class="delimiter">: </span><span class="description">scale a double-precision complex floating-point vector by a double-precision floating-point constant.</span>
 -   <span class="signature">[`zscal( N, alpha, x, strideX )`][@stdlib/blas/base/zscal]</span><span class="delimiter">: </span><span class="description">scales a double-precision complex floating-point vector by a double-precision complex floating-point constant.</span>
 -   <span class="signature">[`zswap( N, x, strideX, y, strideY )`][@stdlib/blas/base/zswap]</span><span class="delimiter">: </span><span class="description">interchange two complex double-precision floating-point vectors.</span>
 

lib/node_modules/@stdlib/ndarray/base/assert/README.md

@@ -78,6 +78,7 @@ var o = ns;
 -   <span class="signature">[`isScalarMostlySafeCompatible( value, dtype )`][@stdlib/ndarray/base/assert/is-scalar-mostly-safe-compatible]</span><span class="delimiter">: </span><span class="description">determine whether a scalar value can be safely cast or, for floating-point data types, downcast to specified ndarray data type.</span>
 -   <span class="signature">[`isSignedIntegerDataType( value )`][@stdlib/ndarray/base/assert/is-signed-integer-data-type]</span><span class="delimiter">: </span><span class="description">test if an input value is a supported ndarray signed integer data type.</span>
 -   <span class="signature">[`isSingleSegmentCompatible( shape, strides, offset )`][@stdlib/ndarray/base/assert/is-single-segment-compatible]</span><span class="delimiter">: </span><span class="description">determine if an array is compatible with a single memory segment.</span>
+-   <span class="signature">[`isStructDataType( value )`][@stdlib/ndarray/base/assert/is-struct-data-type]</span><span class="delimiter">: </span><span class="description">test if an input value is a supported ndarray struct data type.</span>
 -   <span class="signature">[`isUnsignedIntegerDataType( value )`][@stdlib/ndarray/base/assert/is-unsigned-integer-data-type]</span><span class="delimiter">: </span><span class="description">test if an input value is a supported ndarray unsigned integer data type.</span>
 
 </div>
@@ -191,6 +192,8 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/ndarray/base/assert/is-single-segment-compatible]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/assert/is-single-segment-compatible
 
+[@stdlib/ndarray/base/assert/is-struct-data-type]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/assert/is-struct-data-type
+
 [@stdlib/ndarray/base/assert/is-unsigned-integer-data-type]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/assert/is-unsigned-integer-data-type
 
 <!-- </toc-links> -->

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

@@ -115,7 +115,7 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`stdevtk( N, correction, x, stride )`][@stdlib/stats/base/stdevtk]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a strided array using a one-pass textbook algorithm.</span>
 -   <span class="signature">[`stdevwd( N, correction, x, stride )`][@stdlib/stats/base/stdevwd]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a strided array using Welford's algorithm.</span>
 -   <span class="signature">[`stdevyc( N, correction, x, stride )`][@stdlib/stats/base/stdevyc]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a strided array using a one-pass algorithm proposed by Youngs and Cramer.</span>
--   <span class="signature">[`svariance( N, correction, x, stride )`][@stdlib/stats/base/svariance]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array.</span>
+-   <span class="signature">[`svariance( N, correction, x, strideX )`][@stdlib/stats/base/svariance]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array.</span>
 -   <span class="signature">[`svariancewd( N, correction, x, strideX )`][@stdlib/stats/base/svariancewd]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array using Welford's algorithm.</span>
 -   <span class="signature">[`variance( N, correction, x, stride )`][@stdlib/stats/base/variance]</span><span class="delimiter">: </span><span class="description">calculate the variance of a strided array.</span>
 -   <span class="signature">[`variancech( N, correction, x, strideX )`][@stdlib/stats/base/variancech]</span><span class="delimiter">: </span><span class="description">calculate the variance of a strided array using a one-pass trial mean algorithm.</span>