refactor: update paths

Ref: #4797

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---

Author: aayush0325

lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/d.js

@@ -1257,8 +1257,8 @@ ns.push({
 
 ns.push({
 	'alias': 'base.strided.dnanstdevch',
-	'path': '@stdlib/stats/base/dnanstdevch',
-	'value': require( '@stdlib/stats/base/dnanstdevch' ),
+	'path': '@stdlib/stats/strided/dnanstdevch',
+	'value': require( '@stdlib/stats/strided/dnanstdevch' ),
 	'type': 'Function',
 	'related': [
 		'@stdlib/stats/base/dnanstdev',
@@ -2002,7 +2002,7 @@ ns.push({
 	'value': require( '@stdlib/stats/base/dstdevch' ),
 	'type': 'Function',
 	'related': [
-		'@stdlib/stats/base/dnanstdevch',
+		'@stdlib/stats/strided/dnanstdevch',
 		'@stdlib/stats/base/dstdev',
 		'@stdlib/stats/base/dvariancech',
 		'@stdlib/stats/base/sstdevch',

lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/n.js

@@ -253,7 +253,7 @@ ns.push({
 	'value': require( '@stdlib/stats/base/nanstdevch' ),
 	'type': 'Function',
 	'related': [
-		'@stdlib/stats/base/dnanstdevch',
+		'@stdlib/stats/strided/dnanstdevch',
 		'@stdlib/stats/base/nanvariancech',
 		'@stdlib/stats/base/nanstdev',
 		'@stdlib/stats/base/snanstdevch',

lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/s.js

@@ -1229,7 +1229,7 @@ ns.push({
 	'value': require( '@stdlib/stats/base/snanstdevch' ),
 	'type': 'Function',
 	'related': [
-		'@stdlib/stats/base/dnanstdevch',
+		'@stdlib/stats/strided/dnanstdevch',
 		'@stdlib/stats/base/nanstdevch',
 		'@stdlib/stats/base/snanstdev',
 		'@stdlib/stats/base/snanvariancech',

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

@@ -79,7 +79,7 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`dnanmskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/dnanmskrange]</span><span class="delimiter">: </span><span class="description">calculate the range of a double-precision floating-point strided array according to a mask, ignoring `NaN` values.</span>
 -   <span class="signature">[`dnanrange( N, x, strideX )`][@stdlib/stats/strided/dnanrange]</span><span class="delimiter">: </span><span class="description">calculate the range of a double-precision floating-point strided array, ignoring `NaN` values.</span>
 -   <span class="signature">[`dnanstdev( N, correction, x, stride )`][@stdlib/stats/base/dnanstdev]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values.</span>
--   <span class="signature">[`dnanstdevch( N, correction, x, strideX )`][@stdlib/stats/base/dnanstdevch]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass trial mean algorithm.</span>
+-   <span class="signature">[`dnanstdevch( N, correction, x, strideX )`][@stdlib/stats/strided/dnanstdevch]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass trial mean algorithm.</span>
 -   <span class="signature">[`dnanstdevpn( N, correction, x, strideX )`][@stdlib/stats/base/dnanstdevpn]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array, ignoring `NaN` values and using a two-pass algorithm.</span>
 -   <span class="signature">[`dnanstdevtk( N, correction, x, strideX )`][@stdlib/stats/base/dnanstdevtk]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass textbook algorithm.</span>
 -   <span class="signature">[`dnanstdevwd( N, correction, x, strideX )`][@stdlib/stats/base/dnanstdevwd]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using Welford's algorithm.</span>
@@ -343,7 +343,7 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/stats/base/dnanstdev]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dnanstdev
 
-[@stdlib/stats/base/dnanstdevch]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dnanstdevch
+[@stdlib/stats/strided/dnanstdevch]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanstdevch
 
 [@stdlib/stats/base/dnanstdevpn]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dnanstdevpn
 

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

@@ -352,7 +352,7 @@ int main( void ) {
 
 ## See Also
 
--   <span class="package-name">[`@stdlib/stats/base/dnanstdevch`][@stdlib/stats/base/dnanstdevch]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array ignoring NaN values and using a one-pass trial mean algorithm.</span>
+-   <span class="package-name">[`@stdlib/stats/strided/dnanstdevch`][@stdlib/stats/strided/dnanstdevch]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array ignoring NaN values and using a one-pass trial mean algorithm.</span>
 -   <span class="package-name">[`@stdlib/stats/base/dstdev`][@stdlib/stats/base/dstdev]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array.</span>
 -   <span class="package-name">[`@stdlib/stats/base/dvariancech`][@stdlib/stats/base/dvariancech]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array using a one-pass trial mean algorithm.</span>
 -   <span class="package-name">[`@stdlib/stats/base/sstdevch`][@stdlib/stats/base/sstdevch]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a single-precision floating-point strided array using a one-pass trial mean algorithm.</span>
@@ -382,7 +382,7 @@ int main( void ) {
 
 <!-- <related-links> -->
 
-[@stdlib/stats/base/dnanstdevch]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dnanstdevch
+[@stdlib/stats/strided/dnanstdevch]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanstdevch
 
 [@stdlib/stats/base/dstdev]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dstdev
 

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

@@ -183,7 +183,7 @@ var v = nanstdevch.ndarray( N, 1, x, 2, 1 );
 -   If `N <= 0`, both functions return `NaN`.
 -   If `n - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment and `n` corresponds to the number of non-`NaN` indexed elements), both functions return `NaN`.
 -   The underlying algorithm is a specialized case of Neely's two-pass algorithm. As the standard deviation is invariant with respect to changes in the location parameter, the underlying algorithm uses the first strided array element as a trial mean to shift subsequent data values and thus mitigate catastrophic cancellation. Accordingly, the algorithm's accuracy is best when data is **unordered** (i.e., the data is **not** sorted in either ascending or descending order such that the first value is an "extreme" value).
--   Depending on the environment, the typed versions ([`dnanstdevch`][@stdlib/stats/base/dnanstdevch], [`snanstdevch`][@stdlib/stats/base/snanstdevch], etc.) are likely to be significantly more performant.
+-   Depending on the environment, the typed versions ([`dnanstdevch`][@stdlib/stats/strided/dnanstdevch], [`snanstdevch`][@stdlib/stats/base/snanstdevch], etc.) are likely to be significantly more performant.
 
 </section>
 
@@ -241,7 +241,7 @@ console.log( v );
 
 ## See Also
 
--   <span class="package-name">[`@stdlib/stats/base/dnanstdevch`][@stdlib/stats/base/dnanstdevch]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array ignoring NaN values and using a one-pass trial mean algorithm.</span>
+-   <span class="package-name">[`@stdlib/stats/strided/dnanstdevch`][@stdlib/stats/strided/dnanstdevch]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array ignoring NaN values and using a one-pass trial mean algorithm.</span>
 -   <span class="package-name">[`@stdlib/stats/base/nanvariancech`][@stdlib/stats/base/nanvariancech]</span><span class="delimiter">: </span><span class="description">calculate the variance of a strided array ignoring NaN values and using a one-pass trial mean algorithm.</span>
 -   <span class="package-name">[`@stdlib/stats/base/nanstdev`][@stdlib/stats/base/nanstdev]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a strided array ignoring NaN values.</span>
 -   <span class="package-name">[`@stdlib/stats/base/snanstdevch`][@stdlib/stats/base/snanstdevch]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a single-precision floating-point strided array ignoring NaN values and using a one-pass trial mean algorithm.</span>
@@ -271,7 +271,7 @@ console.log( v );
 
 <!-- <related-links> -->
 
-[@stdlib/stats/base/dnanstdevch]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dnanstdevch
+[@stdlib/stats/strided/dnanstdevch]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanstdevch
 
 [@stdlib/stats/base/nanvariancech]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/nanvariancech
 

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

@@ -246,7 +246,7 @@ console.log( v );
 
 ## See Also
 
--   <span class="package-name">[`@stdlib/stats/base/dnanstdevch`][@stdlib/stats/base/dnanstdevch]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array ignoring NaN values and using a one-pass trial mean algorithm.</span>
+-   <span class="package-name">[`@stdlib/stats/strided/dnanstdevch`][@stdlib/stats/strided/dnanstdevch]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a double-precision floating-point strided array ignoring NaN values and using a one-pass trial mean algorithm.</span>
 -   <span class="package-name">[`@stdlib/stats/base/nanstdevch`][@stdlib/stats/base/nanstdevch]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a strided array ignoring NaN values and using a one-pass trial mean algorithm.</span>
 -   <span class="package-name">[`@stdlib/stats/base/snanstdev`][@stdlib/stats/base/snanstdev]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a single-precision floating-point strided array ignoring NaN values.</span>
 -   <span class="package-name">[`@stdlib/stats/base/snanvariancech`][@stdlib/stats/base/snanvariancech]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array ignoring NaN values and using a one-pass trial mean algorithm.</span>
@@ -276,7 +276,7 @@ console.log( v );
 
 <!-- <related-links> -->
 
-[@stdlib/stats/base/dnanstdevch]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dnanstdevch
+[@stdlib/stats/strided/dnanstdevch]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanstdevch
 
 [@stdlib/stats/base/nanstdevch]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/nanstdevch