docs: update namespace table of contents

PR-URL: #4796

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

Author: stdlib-bot

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

@@ -124,10 +124,10 @@ var ns = extblas;
 -   <span class="signature">[`sapx( N, alpha, x, stride )`][@stdlib/blas/ext/base/sapx]</span><span class="delimiter">: </span><span class="description">add a constant to each element in a single-precision floating-point strided array.</span>
 -   <span class="signature">[`sapxsum( N, alpha, x, stride )`][@stdlib/blas/ext/base/sapxsum]</span><span class="delimiter">: </span><span class="description">add a constant to each single-precision floating-point strided array element and compute the sum.</span>
 -   <span class="signature">[`sapxsumkbn( N, alpha, x, stride )`][@stdlib/blas/ext/base/sapxsumkbn]</span><span class="delimiter">: </span><span class="description">add a constant to each single-precision floating-point strided array element and compute the sum using an improved Kahan–Babuška algorithm.</span>
--   <span class="signature">[`sapxsumkbn2( N, alpha, x, stride )`][@stdlib/blas/ext/base/sapxsumkbn2]</span><span class="delimiter">: </span><span class="description">add a constant to each single-precision floating-point strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm.</span>
+-   <span class="signature">[`sapxsumkbn2( N, alpha, x, strideX )`][@stdlib/blas/ext/base/sapxsumkbn2]</span><span class="delimiter">: </span><span class="description">add a scalar constant to each single-precision floating-point strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm.</span>
 -   <span class="signature">[`sapxsumors( N, alpha, x, strideX )`][@stdlib/blas/ext/base/sapxsumors]</span><span class="delimiter">: </span><span class="description">add a scalar constant to each single-precision floating-point strided array element and compute the sum using ordinary recursive summation.</span>
--   <span class="signature">[`sapxsumpw( N, alpha, x, stride )`][@stdlib/blas/ext/base/sapxsumpw]</span><span class="delimiter">: </span><span class="description">add a constant to each single-precision floating-point strided array element and compute the sum using pairwise summation.</span>
--   <span class="signature">[`sasumpw( N, x, stride )`][@stdlib/blas/ext/base/sasumpw]</span><span class="delimiter">: </span><span class="description">calculate the sum of absolute values (_L1_ norm) of single-precision floating-point strided array elements using pairwise summation.</span>
+-   <span class="signature">[`sapxsumpw( N, alpha, x, strideX )`][@stdlib/blas/ext/base/sapxsumpw]</span><span class="delimiter">: </span><span class="description">add a scalar constant to each single-precision floating-point strided array element and compute the sum using pairwise summation.</span>
+-   <span class="signature">[`sasumpw( N, x, strideX )`][@stdlib/blas/ext/base/sasumpw]</span><span class="delimiter">: </span><span class="description">calculate the sum of absolute values (_L1_ norm) of single-precision floating-point strided array elements using pairwise summation.</span>
 -   <span class="signature">[`scusum( N, sum, x, strideX, y, strideY )`][@stdlib/blas/ext/base/scusum]</span><span class="delimiter">: </span><span class="description">calculate the cumulative sum of single-precision floating-point strided array elements.</span>
 -   <span class="signature">[`scusumkbn( N, sum, x, strideX, y, strideY )`][@stdlib/blas/ext/base/scusumkbn]</span><span class="delimiter">: </span><span class="description">calculate the cumulative sum of single-precision floating-point strided array elements using an improved Kahan–Babuška algorithm.</span>
 -   <span class="signature">[`scusumkbn2( N, sum, x, strideX, y, strideY )`][@stdlib/blas/ext/base/scusumkbn2]</span><span class="delimiter">: </span><span class="description">calculate the cumulative sum of single-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm.</span>

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

@@ -70,13 +70,13 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`dmaxabssorted( N, x, strideX )`][@stdlib/stats/base/dmaxabssorted]</span><span class="delimiter">: </span><span class="description">calculate the maximum absolute value of a sorted double-precision floating-point strided array.</span>
 -   <span class="signature">[`dmaxsorted( N, x, strideX )`][@stdlib/stats/base/dmaxsorted]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a sorted double-precision floating-point strided array.</span>
 -   <span class="signature">[`dmean( N, x, stride )`][@stdlib/stats/base/dmean]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array.</span>
--   <span class="signature">[`dmeankbn( N, x, stride )`][@stdlib/stats/base/dmeankbn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm.</span>
+-   <span class="signature">[`dmeankbn( N, x, strideX )`][@stdlib/stats/base/dmeankbn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm.</span>
 -   <span class="signature">[`dmeankbn2( N, x, strideX )`][@stdlib/stats/base/dmeankbn2]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm.</span>
--   <span class="signature">[`dmeanli( N, x, stride )`][@stdlib/stats/base/dmeanli]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm.</span>
+-   <span class="signature">[`dmeanli( N, x, strideX )`][@stdlib/stats/base/dmeanli]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm.</span>
 -   <span class="signature">[`dmeanlipw( N, x, stride )`][@stdlib/stats/base/dmeanlipw]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm with pairwise summation.</span>
--   <span class="signature">[`dmeanors( N, x, stride )`][@stdlib/stats/base/dmeanors]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using ordinary recursive summation.</span>
+-   <span class="signature">[`dmeanors( N, x, strideX )`][@stdlib/stats/base/dmeanors]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using ordinary recursive summation.</span>
 -   <span class="signature">[`dmeanpn( N, x, stride )`][@stdlib/stats/base/dmeanpn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using a two-pass error correction algorithm.</span>
--   <span class="signature">[`dmeanpw( N, x, stride )`][@stdlib/stats/base/dmeanpw]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using pairwise summation.</span>
+-   <span class="signature">[`dmeanpw( N, x, strideX )`][@stdlib/stats/base/dmeanpw]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using pairwise summation.</span>
 -   <span class="signature">[`dmeanstdev( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/base/dmeanstdev]</span><span class="delimiter">: </span><span class="description">calculate the mean and standard deviation of a double-precision floating-point strided array.</span>
 -   <span class="signature">[`dmeanstdevpn( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/base/dmeanstdevpn]</span><span class="delimiter">: </span><span class="description">calculate the mean and standard deviation of a double-precision floating-point strided array using a two-pass algorithm.</span>
 -   <span class="signature">[`dmeanvar( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/base/dmeanvar]</span><span class="delimiter">: </span><span class="description">calculate the mean and variance of a double-precision floating-point strided array.</span>
@@ -117,11 +117,11 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`dnanvarianceyc( N, correction, x, stride )`][@stdlib/stats/base/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">[`drange( N, x, strideX )`][@stdlib/stats/base/drange]</span><span class="delimiter">: </span><span class="description">calculate the range of a double-precision floating-point strided array.</span>
 -   <span class="signature">[`dsem( N, correction, x, stride )`][@stdlib/stats/base/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>
--   <span class="signature">[`dsemch( N, correction, x, stride )`][@stdlib/stats/base/dsemch]</span><span class="delimiter">: </span><span class="description">calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass trial mean algorithm.</span>
+-   <span class="signature">[`dsemch( N, correction, x, strideX )`][@stdlib/stats/base/dsemch]</span><span class="delimiter">: </span><span class="description">calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass trial mean algorithm.</span>
 -   <span class="signature">[`dsempn( N, correction, x, stride )`][@stdlib/stats/base/dsempn]</span><span class="delimiter">: </span><span class="description">calculate the standard error of the mean of a double-precision floating-point strided array using a two-pass algorithm.</span>
--   <span class="signature">[`dsemtk( N, correction, x, stride )`][@stdlib/stats/base/dsemtk]</span><span class="delimiter">: </span><span class="description">calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass textbook algorithm.</span>
+-   <span class="signature">[`dsemtk( N, correction, x, strideX )`][@stdlib/stats/base/dsemtk]</span><span class="delimiter">: </span><span class="description">calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass textbook algorithm.</span>
 -   <span class="signature">[`dsemwd( N, correction, x, strideX )`][@stdlib/stats/base/dsemwd]</span><span class="delimiter">: </span><span class="description">calculate the standard error of the mean of a double-precision floating-point strided array using Welford's algorithm.</span>
--   <span class="signature">[`dsemyc( N, correction, x, stride )`][@stdlib/stats/base/dsemyc]</span><span class="delimiter">: </span><span class="description">calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer.</span>
+-   <span class="signature">[`dsemyc( N, correction, x, strideX )`][@stdlib/stats/base/dsemyc]</span><span class="delimiter">: </span><span class="description">calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer.</span>
 -   <span class="signature">[`dsmean( N, x, stride )`][@stdlib/stats/base/dsmean]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using extended accumulation and returning an extended precision result.</span>
 -   <span class="signature">[`dsmeanors( N, x, stride )`][@stdlib/stats/base/dsmeanors]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and returning an extended precision result.</span>
 -   <span class="signature">[`dsmeanpn( N, x, stride )`][@stdlib/stats/base/dsmeanpn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and returning an extended precision result.</span>
@@ -201,7 +201,7 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`scumin( N, x, strideX, y, strideY )`][@stdlib/stats/base/scumin]</span><span class="delimiter">: </span><span class="description">calculate the cumulative minimum of single-precision floating-point strided array elements.</span>
 -   <span class="signature">[`scuminabs( N, x, strideX, y, strideY )`][@stdlib/stats/base/scuminabs]</span><span class="delimiter">: </span><span class="description">calculate the cumulative minimum absolute value of single-precision floating-point strided array elements.</span>
 -   <span class="signature">[`sdsmean( N, x, stride )`][@stdlib/stats/base/sdsmean]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using extended accumulation.</span>
--   <span class="signature">[`sdsmeanors( N, x, stride )`][@stdlib/stats/base/sdsmeanors]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation.</span>
+-   <span class="signature">[`sdsmeanors( N, x, strideX )`][@stdlib/stats/base/sdsmeanors]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation.</span>
 -   <span class="signature">[`sdsnanmean( N, x, stride )`][@stdlib/stats/base/sdsnanmean]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using extended accumulation.</span>
 -   <span class="signature">[`sdsnanmeanors( N, x, stride )`][@stdlib/stats/base/sdsnanmeanors]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using ordinary recursive summation with extended accumulation.</span>
 -   <span class="signature">[`smax( N, x, strideX )`][@stdlib/stats/base/smax]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a single-precision floating-point strided array.</span>
@@ -267,7 +267,7 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`svariancepn( N, correction, x, stride )`][@stdlib/stats/base/svariancepn]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array using a two-pass algorithm.</span>
 -   <span class="signature">[`svariancetk( N, correction, x, strideX )`][@stdlib/stats/base/svariancetk]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array using a one-pass textbook algorithm.</span>
 -   <span class="signature">[`svariancewd( N, correction, x, stride )`][@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">[`svarianceyc( N, correction, x, stride )`][@stdlib/stats/base/svarianceyc]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer.</span>
+-   <span class="signature">[`svarianceyc( N, correction, x, strideX )`][@stdlib/stats/base/svarianceyc]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer.</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, stride )`][@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>
 -   <span class="signature">[`variancepn( N, correction, x, stride )`][@stdlib/stats/base/variancepn]</span><span class="delimiter">: </span><span class="description">calculate the variance of a strided array using a two-pass algorithm.</span>