You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Copy file name to clipboardExpand all lines: lib/node_modules/@stdlib/blas/ext/base/README.md
+1-1Lines changed: 1 addition & 1 deletion
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -143,7 +143,7 @@ var ns = extblas;
143
143
- <spanclass="signature">[`snansum( N, x, stride )`][@stdlib/blas/ext/base/snansum]</span><spanclass="delimiter">: </span><spanclass="description">calculate the sum of single-precision floating-point strided array elements, ignoring `NaN` values.</span>
144
144
- <spanclass="signature">[`snansumkbn( N, x, stride )`][@stdlib/blas/ext/base/snansumkbn]</span><spanclass="delimiter">: </span><spanclass="description">calculate the sum of single-precision floating-point strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm.</span>
145
145
- <spanclass="signature">[`snansumkbn2( N, x, stride )`][@stdlib/blas/ext/base/snansumkbn2]</span><spanclass="delimiter">: </span><spanclass="description">calculate the sum of single-precision floating-point strided array elements, ignoring `NaN` values and using a second-order iterative Kahan–Babuška algorithm.</span>
146
-
- <spanclass="signature">[`snansumors( N, x, stride )`][@stdlib/blas/ext/base/snansumors]</span><spanclass="delimiter">: </span><spanclass="description">calculate the sum of single-precision floating-point strided array elements, ignoring `NaN` values and using ordinary recursive summation.</span>
146
+
- <spanclass="signature">[`snansumors( N, x, strideX )`][@stdlib/blas/ext/base/snansumors]</span><spanclass="delimiter">: </span><spanclass="description">calculate the sum of single-precision floating-point strided array elements, ignoring `NaN` values and using ordinary recursive summation.</span>
147
147
- <spanclass="signature">[`snansumpw( N, x, strideX )`][@stdlib/blas/ext/base/snansumpw]</span><spanclass="delimiter">: </span><spanclass="description">calculate the sum of single-precision floating-point strided array elements, ignoring `NaN` values and using pairwise summation.</span>
148
148
- <spanclass="signature">[`srev( N, x, stride )`][@stdlib/blas/ext/base/srev]</span><spanclass="delimiter">: </span><spanclass="description">reverse a single-precision floating-point strided array in-place.</span>
149
149
- <spanclass="signature">[`ssort2hp( N, order, x, strideX, y, strideY )`][@stdlib/blas/ext/base/ssort2hp]</span><spanclass="delimiter">: </span><spanclass="description">simultaneously sort two single-precision floating-point strided arrays based on the sort order of the first array using heapsort.</span>
Copy file name to clipboardExpand all lines: lib/node_modules/@stdlib/stats/base/README.md
+3-3Lines changed: 3 additions & 3 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -85,7 +85,7 @@ The namespace contains the following statistical functions:
85
85
- <spanclass="signature">[`dmediansorted( N, x, stride )`][@stdlib/stats/base/dmediansorted]</span><spanclass="delimiter">: </span><spanclass="description">calculate the median value of a sorted double-precision floating-point strided array.</span>
86
86
- <spanclass="signature">[`dmidrange( N, x, stride )`][@stdlib/stats/base/dmidrange]</span><spanclass="delimiter">: </span><spanclass="description">calculate the mid-range of a double-precision floating-point strided array.</span>
87
87
- <spanclass="signature">[`dmin( N, x, stride )`][@stdlib/stats/base/dmin]</span><spanclass="delimiter">: </span><spanclass="description">calculate the minimum value of a double-precision floating-point strided array.</span>
88
-
- <spanclass="signature">[`dminabs( N, x, stride )`][@stdlib/stats/base/dminabs]</span><spanclass="delimiter">: </span><spanclass="description">calculate the minimum absolute value of a double-precision floating-point strided array.</span>
88
+
- <spanclass="signature">[`dminabs( N, x, strideX )`][@stdlib/stats/base/dminabs]</span><spanclass="delimiter">: </span><spanclass="description">calculate the minimum absolute value of a double-precision floating-point strided array.</span>
89
89
- <spanclass="signature">[`dminsorted( N, x, stride )`][@stdlib/stats/base/dminsorted]</span><spanclass="delimiter">: </span><spanclass="description">calculate the minimum value of a sorted double-precision floating-point strided array.</span>
90
90
- <spanclass="signature">[`dmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/dmskmax]</span><spanclass="delimiter">: </span><spanclass="description">calculate the maximum value of a double-precision floating-point strided array according to a mask.</span>
91
91
- <spanclass="signature">[`dmskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/dmskmin]</span><spanclass="delimiter">: </span><spanclass="description">calculate the minimum value of a double-precision floating-point strided array according to a mask.</span>
@@ -98,7 +98,7 @@ The namespace contains the following statistical functions:
98
98
- <spanclass="signature">[`dnanmeanpw( N, x, stride )`][@stdlib/stats/base/dnanmeanpw]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using pairwise summation.</span>
99
99
- <spanclass="signature">[`dnanmeanwd( N, x, stride )`][@stdlib/stats/base/dnanmeanwd]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a double-precision floating-point strided array, using Welford's algorithm and ignoring `NaN` values.</span>
100
100
- <spanclass="signature">[`dnanmin( N, x, stride )`][@stdlib/stats/base/dnanmin]</span><spanclass="delimiter">: </span><spanclass="description">calculate the minimum value of a double-precision floating-point strided array, ignoring `NaN` values.</span>
101
-
- <spanclass="signature">[`dnanminabs( N, x, stride )`][@stdlib/stats/base/dnanminabs]</span><spanclass="delimiter">: </span><spanclass="description">calculate the minimum absolute value of a double-precision floating-point strided array, ignoring `NaN` values.</span>
101
+
- <spanclass="signature">[`dnanminabs( N, x, strideX )`][@stdlib/stats/base/dnanminabs]</span><spanclass="delimiter">: </span><spanclass="description">calculate the minimum absolute value of a double-precision floating-point strided array, ignoring `NaN` values.</span>
102
102
- <spanclass="signature">[`dnanmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/dnanmskmax]</span><spanclass="delimiter">: </span><spanclass="description">calculate the maximum value of a double-precision floating-point strided array according to a mask, ignoring `NaN` values.</span>
103
103
- <spanclass="signature">[`dnanmskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/dnanmskmin]</span><spanclass="delimiter">: </span><spanclass="description">calculate the minimum value of a double-precision floating-point strided array according to a mask, ignoring `NaN` values.</span>
104
104
- <spanclass="signature">[`dnanmskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/dnanmskrange]</span><spanclass="delimiter">: </span><spanclass="description">calculate the range of a double-precision floating-point strided array according to a mask, ignoring `NaN` values.</span>
@@ -115,7 +115,7 @@ The namespace contains the following statistical functions:
115
115
- <spanclass="signature">[`dnanvariancetk( N, correction, x, stride )`][@stdlib/stats/base/dnanvariancetk]</span><spanclass="delimiter">: </span><spanclass="description">calculate the variance of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass textbook algorithm.</span>
116
116
- <spanclass="signature">[`dnanvariancewd( N, correction, x, stride )`][@stdlib/stats/base/dnanvariancewd]</span><spanclass="delimiter">: </span><spanclass="description">calculate the variance of a double-precision floating-point strided array ignoring `NaN` values and using Welford's algorithm.</span>
117
117
- <spanclass="signature">[`dnanvarianceyc( N, correction, x, stride )`][@stdlib/stats/base/dnanvarianceyc]</span><spanclass="delimiter">: </span><spanclass="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>
118
-
- <spanclass="signature">[`drange( N, x, stride )`][@stdlib/stats/base/drange]</span><spanclass="delimiter">: </span><spanclass="description">calculate the range of a double-precision floating-point strided array.</span>
118
+
- <spanclass="signature">[`drange( N, x, strideX )`][@stdlib/stats/base/drange]</span><spanclass="delimiter">: </span><spanclass="description">calculate the range of a double-precision floating-point strided array.</span>
119
119
- <spanclass="signature">[`dsem( N, correction, x, stride )`][@stdlib/stats/base/dsem]</span><spanclass="delimiter">: </span><spanclass="description">calculate the standard error of the mean of a double-precision floating-point strided array.</span>
120
120
- <spanclass="signature">[`dsemch( N, correction, x, stride )`][@stdlib/stats/base/dsemch]</span><spanclass="delimiter">: </span><spanclass="description">calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass trial mean algorithm.</span>
121
121
- <spanclass="signature">[`dsempn( N, correction, x, stride )`][@stdlib/stats/base/dsempn]</span><spanclass="delimiter">: </span><spanclass="description">calculate the standard error of the mean of a double-precision floating-point strided array using a two-pass algorithm.</span>
0 commit comments