docs: update namespace table of contents

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

@@ -90,6 +90,7 @@ The namespace exports the following:
 -   <span class="signature">[`dmskmidrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dmskmidrange]</span><span class="delimiter">: </span><span class="description">calculate the mid-range of a double-precision floating-point strided array according to a mask.</span>
 -   <span class="signature">[`dmskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dmskmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a double-precision floating-point strided array according to a mask.</span>
 -   <span class="signature">[`dmskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dmskrange]</span><span class="delimiter">: </span><span class="description">calculate the range of a double-precision floating-point strided array according to a mask.</span>
+-   <span class="signature">[`dnancount( N, x, strideX )`][@stdlib/stats/strided/dnancount]</span><span class="delimiter">: </span><span class="description">calculate the number of non-`NaN` elements in a double-precision floating-point strided array.</span>
 -   <span class="signature">[`dnanmax( N, x, strideX )`][@stdlib/stats/strided/dnanmax]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a double-precision floating-point strided array, ignoring `NaN` values.</span>
 -   <span class="signature">[`dnanmaxabs( N, x, strideX )`][@stdlib/stats/strided/dnanmaxabs]</span><span class="delimiter">: </span><span class="description">calculate the maximum absolute value of a double-precision floating-point strided array, ignoring `NaN` values.</span>
 -   <span class="signature">[`dnanmean( N, x, strideX )`][@stdlib/stats/strided/dnanmean]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values.</span>
@@ -101,10 +102,13 @@ The namespace exports the following:
 -   <span class="signature">[`dnanmin( N, x, strideX )`][@stdlib/stats/strided/dnanmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a double-precision floating-point strided array, ignoring `NaN` values.</span>
 -   <span class="signature">[`dnanminabs( N, x, strideX )`][@stdlib/stats/strided/dnanminabs]</span><span class="delimiter">: </span><span class="description">calculate the minimum absolute value of a double-precision floating-point strided array, ignoring `NaN` values.</span>
 -   <span class="signature">[`dnanmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dnanmskmax]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a double-precision floating-point strided array according to a mask, ignoring `NaN` values.</span>
+-   <span class="signature">[`dnanmskmaxabs( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dnanmskmaxabs]</span><span class="delimiter">: </span><span class="description">calculate the maximum absolute value of a double-precision floating-point strided array according to a mask, ignoring `NaN` values.</span>
 -   <span class="signature">[`dnanmskmidrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dnanmskmidrange]</span><span class="delimiter">: </span><span class="description">calculate the mid-range of a double-precision floating-point strided array according to a mask, ignoring `NaN` values.</span>
 -   <span class="signature">[`dnanmskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dnanmskmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a double-precision floating-point strided array according to a mask, ignoring `NaN` values.</span>
+-   <span class="signature">[`dnanmskminabs( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/dnanmskminabs]</span><span class="delimiter">: </span><span class="description">calculate the minimum absolute value of a double-precision floating-point strided array according to a mask, ignoring `NaN` values.</span>
 -   <span class="signature">[`dnanmskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/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">[`dnanrangeabs( N, \*X, strideX )`][@stdlib/stats/strided/dnanrangeabs]</span><span class="delimiter">: </span><span class="description">compute the range of absolute values of a double-precision floating-point strided array, ignoring `NaN` values.</span>
 -   <span class="signature">[`dnanstdev( N, correction, x, strideX )`][@stdlib/stats/strided/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/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/strided/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>
@@ -117,6 +121,7 @@ The namespace exports the following:
 -   <span class="signature">[`dnanvariancetk( N, correction, x, strideX )`][@stdlib/stats/strided/dnanvariancetk]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass textbook algorithm.</span>
 -   <span class="signature">[`dnanvariancewd( N, correction, x, strideX )`][@stdlib/stats/strided/dnanvariancewd]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array ignoring `NaN` values and using Welford's algorithm.</span>
 -   <span class="signature">[`dnanvarianceyc( N, correction, x, strideX )`][@stdlib/stats/strided/dnanvarianceyc]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer.</span>
+-   <span class="signature">[`dpcorrwd( N, x, strideX, y, strideY )`][@stdlib/stats/strided/dpcorrwd]</span><span class="delimiter">: </span><span class="description">calculate the sample Pearson product-moment correlation coefficient of two double-precision floating-point strided arrays using Welford's algorithm.</span>
 -   <span class="signature">[`drange( N, x, strideX )`][@stdlib/stats/strided/drange]</span><span class="delimiter">: </span><span class="description">calculate the range of a double-precision floating-point strided array.</span>
 -   <span class="signature">[`drangeabs( N, x, strideX )`][@stdlib/stats/strided/drangeabs]</span><span class="delimiter">: </span><span class="description">compute the range of absolute values of a double-precision floating-point strided array.</span>
 -   <span class="signature">[`dsem( N, correction, x, strideX )`][@stdlib/stats/strided/dsem]</span><span class="delimiter">: </span><span class="description">calculate the standard error of the mean of a double-precision floating-point strided array.</span>
@@ -175,7 +180,9 @@ The namespace exports the following:
 -   <span class="signature">[`mskmaxabs( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/mskmaxabs]</span><span class="delimiter">: </span><span class="description">calculate the maximum absolute value of a strided array according to a mask.</span>
 -   <span class="signature">[`mskmidrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/mskmidrange]</span><span class="delimiter">: </span><span class="description">calculate the mid-range of a strided array according to a mask.</span>
 -   <span class="signature">[`mskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/mskmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a strided array according to a mask.</span>
+-   <span class="signature">[`mskminabs( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/mskminabs]</span><span class="delimiter">: </span><span class="description">calculate the minimum absolute value of a strided array according to a mask.</span>
 -   <span class="signature">[`mskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/mskrange]</span><span class="delimiter">: </span><span class="description">calculate the range of a strided array according to a mask.</span>
+-   <span class="signature">[`nancount( N, x, strideX )`][@stdlib/stats/strided/nancount]</span><span class="delimiter">: </span><span class="description">calculate the number of non-`NaN` elements in a strided array.</span>
 -   <span class="signature">[`nanmaxBy( N, x, strideX, clbk[, thisArg] )`][@stdlib/stats/strided/nanmax-by]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a strided array via a callback function, ignoring `NaN` values.</span>
 -   <span class="signature">[`nanmax( N, x, strideX )`][@stdlib/stats/strided/nanmax]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a strided array, ignoring `NaN` values.</span>
 -   <span class="signature">[`nanmaxabs( N, x, strideX )`][@stdlib/stats/strided/nanmaxabs]</span><span class="delimiter">: </span><span class="description">calculate the maximum absolute value of a strided array, ignoring `NaN` values.</span>
@@ -194,6 +201,7 @@ The namespace exports the following:
 -   <span class="signature">[`nanmskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/nanmskrange]</span><span class="delimiter">: </span><span class="description">calculate the range of a strided array according to a mask, ignoring `NaN` values.</span>
 -   <span class="signature">[`nanrangeBy( N, x, strideX, clbk[, thisArg] )`][@stdlib/stats/strided/nanrange-by]</span><span class="delimiter">: </span><span class="description">calculate the range of a strided array via a callback function, ignoring `NaN` values.</span>
 -   <span class="signature">[`nanrange( N, x, strideX )`][@stdlib/stats/strided/nanrange]</span><span class="delimiter">: </span><span class="description">calculate the range of a strided array, ignoring `NaN` values.</span>
+-   <span class="signature">[`nanrangeabs( N, x, strideX )`][@stdlib/stats/strided/nanrangeabs]</span><span class="delimiter">: </span><span class="description">calculate the range of absolute values of a strided array, ignoring `NaN` values.</span>
 -   <span class="signature">[`nanstdev( N, correction, x, strideX )`][@stdlib/stats/strided/nanstdev]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a strided array ignoring `NaN` values.</span>
 -   <span class="signature">[`nanstdevch( N, correction, x, strideX )`][@stdlib/stats/strided/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="signature">[`nanstdevpn( N, correction, x, strideX )`][@stdlib/stats/strided/nanstdevpn]</span><span class="delimiter">: </span><span class="description">calculate the standard deviation of a strided array ignoring `NaN` values and using a two-pass algorithm.</span>
@@ -250,8 +258,10 @@ The namespace exports the following:
 -   <span class="signature">[`snanmin( N, x, strideX )`][@stdlib/stats/strided/snanmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a single-precision floating-point strided array, ignoring `NaN` values.</span>
 -   <span class="signature">[`snanminabs( N, x, strideX )`][@stdlib/stats/strided/snanminabs]</span><span class="delimiter">: </span><span class="description">calculate the minimum absolute value of a single-precision floating-point strided array, ignoring `NaN` values.</span>
 -   <span class="signature">[`snanmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/snanmskmax]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a single-precision floating-point strided array according to a mask, ignoring `NaN` values.</span>
+-   <span class="signature">[`snanmskmaxabs( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/snanmskmaxabs]</span><span class="delimiter">: </span><span class="description">calculate the maximum absolute value of a single-precision floating-point strided array according to a mask, ignoring `NaN` values.</span>
 -   <span class="signature">[`snanmskmidrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/snanmskmidrange]</span><span class="delimiter">: </span><span class="description">calculate the mid-range of a single-precision floating-point strided array according to a mask, ignoring `NaN` values.</span>
 -   <span class="signature">[`snanmskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/snanmskmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a single-precision floating-point strided array according to a mask, ignoring `NaN` values.</span>
+-   <span class="signature">[`snanmskminabs( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/snanmskminabs]</span><span class="delimiter">: </span><span class="description">calculate the minimum absolute value of a single-precision floating-point strided array according to a mask, ignoring `NaN` values.</span>
 -   <span class="signature">[`snanmskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/strided/snanmskrange]</span><span class="delimiter">: </span><span class="description">calculate the range of a single-precision floating-point strided array according to a mask, ignoring `NaN` values.</span>
 -   <span class="signature">[`snanrange( N, x, strideX )`][@stdlib/stats/strided/snanrange]</span><span class="delimiter">: </span><span class="description">calculate the range of a single-precision floating-point strided array, ignoring `NaN` values.</span>
 -   <span class="signature">[`srange( N, x, strideX )`][@stdlib/stats/strided/srange]</span><span class="delimiter">: </span><span class="description">calculate the range of a single-precision floating-point strided array.</span>
@@ -406,6 +416,8 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/stats/strided/dmskrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmskrange
 
+[@stdlib/stats/strided/dnancount]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnancount
+
 [@stdlib/stats/strided/dnanmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmax
 
 [@stdlib/stats/strided/dnanmaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmaxabs
@@ -428,14 +440,20 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/stats/strided/dnanmskmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmskmax
 
+[@stdlib/stats/strided/dnanmskmaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmskmaxabs
+
 [@stdlib/stats/strided/dnanmskmidrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmskmidrange
 
 [@stdlib/stats/strided/dnanmskmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmskmin
 
+[@stdlib/stats/strided/dnanmskminabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmskminabs
+
 [@stdlib/stats/strided/dnanmskrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmskrange
 
 [@stdlib/stats/strided/dnanrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanrange
 
+[@stdlib/stats/strided/dnanrangeabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanrangeabs
+
 [@stdlib/stats/strided/dnanstdev]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanstdev
 
 [@stdlib/stats/strided/dnanstdevch]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanstdevch
@@ -460,6 +478,8 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/stats/strided/dnanvarianceyc]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanvarianceyc
 
+[@stdlib/stats/strided/dpcorrwd]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dpcorrwd
+
 [@stdlib/stats/strided/drange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/drange
 
 [@stdlib/stats/strided/drangeabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/drangeabs
@@ -576,8 +596,12 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/stats/strided/mskmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/mskmin
 
+[@stdlib/stats/strided/mskminabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/mskminabs
+
 [@stdlib/stats/strided/mskrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/mskrange
 
+[@stdlib/stats/strided/nancount]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nancount
+
 [@stdlib/stats/strided/nanmax-by]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanmax-by
 
 [@stdlib/stats/strided/nanmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanmax
@@ -614,6 +638,8 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/stats/strided/nanrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanrange
 
+[@stdlib/stats/strided/nanrangeabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanrangeabs
+
 [@stdlib/stats/strided/nanstdev]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanstdev
 
 [@stdlib/stats/strided/nanstdevch]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/nanstdevch
@@ -726,10 +752,14 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/stats/strided/snanmskmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanmskmax
 
+[@stdlib/stats/strided/snanmskmaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanmskmaxabs
+
 [@stdlib/stats/strided/snanmskmidrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanmskmidrange
 
 [@stdlib/stats/strided/snanmskmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanmskmin
 
+[@stdlib/stats/strided/snanmskminabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanmskminabs
+
 [@stdlib/stats/strided/snanmskrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanmskrange
 
 [@stdlib/stats/strided/snanrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanrange