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Author: stdlib-bot

CHANGELOG.md

@@ -4,7 +4,7 @@
 
 <section class="release" id="unreleased">
 
-## Unreleased (2025-06-13)
+## Unreleased (2025-06-14)
 
 <section class="features">
 
@@ -56,6 +56,7 @@ A total of 2 issues were closed in this release:
 
 <details>
 
+-   [`5f5177b`](https://github.com/stdlib-js/stdlib/commit/5f5177bb8f8ae117b58bd0959f1c51b6939c4c78) - **docs:** update REPL namespace documentation [(#7353)](https://github.com/stdlib-js/stdlib/pull/7353) _(by stdlib-bot)_
 -   [`5e6b517`](https://github.com/stdlib-js/stdlib/commit/5e6b5173a0fdd3d50d79125f66dafb7bc13a4bf7) - **docs:** update REPL namespace documentation [(#7339)](https://github.com/stdlib-js/stdlib/pull/7339) _(by stdlib-bot)_
 -   [`00f8cc6`](https://github.com/stdlib-js/stdlib/commit/00f8cc65988a12dcaf37604a885934e8fc73a94e) - **docs:** update REPL namespace documentation [(#7329)](https://github.com/stdlib-js/stdlib/pull/7329) _(by stdlib-bot)_
 -   [`88e6d2f`](https://github.com/stdlib-js/stdlib/commit/88e6d2fb7a4c0e2b4bc767588467080459dcc730) - **docs:** update REPL namespace documentation [(#7314)](https://github.com/stdlib-js/stdlib/pull/7314) _(by stdlib-bot)_

code-blocks/data/data.csv

@@ -2012,10 +2012,10 @@ base.strided.dvariancewd,"\nbase.strided.dvariancewd( N:integer, correction:numb
 base.strided.dvariancewd.ndarray,"\nbase.strided.dvariancewd.ndarray( N:integer, correction:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n"
 base.strided.dvarianceyc,"\nbase.strided.dvarianceyc( N:integer, correction:number, x:Float64Array, \n  strideX:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer.\n"
 base.strided.dvarianceyc.ndarray,"\nbase.strided.dvarianceyc.ndarray( N:integer, correction:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n"
-base.strided.dvarm,"\nbase.strided.dvarm( N:integer, mean:number, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean.\n"
-base.strided.dvarm.ndarray,"\nbase.strided.dvarm.ndarray( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using alternative indexing semantics.\n"
-base.strided.dvarmpn,"\nbase.strided.dvarmpn( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm.\n"
-base.strided.dvarmpn.ndarray,"\nbase.strided.dvarmpn.ndarray( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm and alternative\n    indexing semantics.\n"
+base.strided.dvarm,"\nbase.strided.dvarm( N:integer, mean:number, correction:number, x:Float64Array, \n  strideX:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean.\n"
+base.strided.dvarm.ndarray,"\nbase.strided.dvarm.ndarray( N:integer, mean:number, correction:number, \n  x:Float64Array, strideX:integer, offsetX:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using alternative indexing semantics.\n"
+base.strided.dvarmpn,"\nbase.strided.dvarmpn( N:integer, mean:number, correction:number, \n  x:Float64Array, strideX:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm.\n"
+base.strided.dvarmpn.ndarray,"\nbase.strided.dvarmpn.ndarray( N:integer, mean:number, correction:number, \n  x:Float64Array, strideX:integer, offsetX:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm and alternative\n    indexing semantics.\n"
 base.strided.dvarmtk,"\nbase.strided.dvarmtk( N:integer, mean:number, correction:number, \n  x:Float64Array, strideX:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using a one-pass textbook algorithm.\n"
 base.strided.dvarmtk.ndarray,"\nbase.strided.dvarmtk.ndarray( N:integer, mean:number, correction:number, \n  x:Float64Array, strideX:integer, offsetX:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n"
 base.strided.gapx,"\nbase.strided.gapx( N:integer, alpha:number, x:Array|TypedArray, \n  strideX:integer )\n    Adds a scalar constant to each element in a strided array.\n"
@@ -2189,8 +2189,8 @@ base.strided.nanstdevyc,"\nbase.strided.nanstdevyc( N:integer, correction:number
 base.strided.nanstdevyc.ndarray,"\nbase.strided.nanstdevyc.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n"
 base.strided.nanvariance,"\nbase.strided.nanvariance( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values.\n"
 base.strided.nanvariance.ndarray,"\nbase.strided.nanvariance.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    alternative indexing semantics.\n"
-base.strided.nanvariancech,"\nbase.strided.nanvariancech( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm.\n"
-base.strided.nanvariancech.ndarray,"\nbase.strided.nanvariancech.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm and alternative indexing semantics.\n"
+base.strided.nanvariancech,"\nbase.strided.nanvariancech( N:integer, correction:number, x:Array|TypedArray, \n  strideX:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm.\n"
+base.strided.nanvariancech.ndarray,"\nbase.strided.nanvariancech.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, strideX:integer, offsetX:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm and alternative indexing semantics.\n"
 base.strided.nanvariancepn,"\nbase.strided.nanvariancepn( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    two-pass algorithm.\n"
 base.strided.nanvariancepn.ndarray,"\nbase.strided.nanvariancepn.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    two-pass algorithm and alternative indexing semantics.\n"
 base.strided.nanvariancetk,"\nbase.strided.nanvariancetk( N:integer, correction:number, x:Array|TypedArray, \n  strideX:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass textbook algorithm.\n"
@@ -2471,12 +2471,12 @@ base.strided.ssumpw,"\nbase.strided.ssumpw( N:integer, x:Float32Array, strideX:i
 base.strided.ssumpw.ndarray,"\nbase.strided.ssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n"
 base.strided.sswap,"\nbase.strided.sswap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Interchanges two single-precision floating-point vectors.\n"
 base.strided.sswap.ndarray,"\nbase.strided.sswap.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Interchanges two single-precision floating-point vectors using alternative\n    indexing semantics.\n"
-base.strided.stdev,"\nbase.strided.stdev( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array.\n"
-base.strided.stdev.ndarray,"\nbase.strided.stdev.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using alternative\n    indexing semantics.\n"
-base.strided.stdevch,"\nbase.strided.stdevch( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm.\n"
-base.strided.stdevch.ndarray,"\nbase.strided.stdevch.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm and alternative indexing semantics.\n"
-base.strided.stdevpn,"\nbase.strided.stdevpn( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm.\n"
-base.strided.stdevpn.ndarray,"\nbase.strided.stdevpn.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm and alternative indexing semantics.\n"
+base.strided.stdev,"\nbase.strided.stdev( N:integer, correction:number, x:Array|TypedArray, \n  strideX:integer )\n    Computes the standard deviation of a strided array.\n"
+base.strided.stdev.ndarray,"\nbase.strided.stdev.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer )\n    Computes the standard deviation of a strided array using alternative\n    indexing semantics.\n"
+base.strided.stdevch,"\nbase.strided.stdevch( N:integer, correction:number, x:Array|TypedArray, \n  strideX:integer )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm.\n"
+base.strided.stdevch.ndarray,"\nbase.strided.stdevch.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm and alternative indexing semantics.\n"
+base.strided.stdevpn,"\nbase.strided.stdevpn( N:integer, correction:number, x:Array|TypedArray, \n  strideX:integer )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm.\n"
+base.strided.stdevpn.ndarray,"\nbase.strided.stdevpn.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm and alternative indexing semantics.\n"
 base.strided.stdevtk,"\nbase.strided.stdevtk( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using a one-pass textbook\n    algorithm.\n"
 base.strided.stdevtk.ndarray,"\nbase.strided.stdevtk.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using a one-pass textbook\n    algorithm and alternative indexing semantics.\n"
 base.strided.stdevwd,"\nbase.strided.stdevwd( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using Welford's\n    algorithm.\n"
@@ -2507,10 +2507,10 @@ base.strided.unaryDtypeSignatures,"\nbase.strided.unaryDtypeSignatures( dtypes1:
 base.strided.unarySignatureCallbacks,"\nbase.strided.unarySignatureCallbacks( table:Object, signatures:ArrayLike<any> )\n    Assigns callbacks to unary interfaces according to type promotion rules.\n"
 base.strided.variance,"\nbase.strided.variance( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array.\n"
 base.strided.variance.ndarray,"\nbase.strided.variance.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using alternative indexing\n    semantics.\n"
-base.strided.variancech,"\nbase.strided.variancech( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm.\n"
-base.strided.variancech.ndarray,"\nbase.strided.variancech.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm and alternative indexing semantics.\n"
-base.strided.variancepn,"\nbase.strided.variancepn( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using a two-pass algorithm.\n"
-base.strided.variancepn.ndarray,"\nbase.strided.variancepn.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using a two-pass algorithm and\n    alternative indexing semantics.\n"
+base.strided.variancech,"\nbase.strided.variancech( N:integer, correction:number, x:Array|TypedArray, \n  strideX:integer )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm.\n"
+base.strided.variancech.ndarray,"\nbase.strided.variancech.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, strideX:integer, offsetX:integer )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm and alternative indexing semantics.\n"
+base.strided.variancepn,"\nbase.strided.variancepn( N:integer, correction:number, x:Array|TypedArray, \n  strideX:integer )\n    Computes the variance of a strided array using a two-pass algorithm.\n"
+base.strided.variancepn.ndarray,"\nbase.strided.variancepn.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, strideX:integer, offsetX:integer )\n    Computes the variance of a strided array using a two-pass algorithm and\n    alternative indexing semantics.\n"
 base.strided.variancetk,"\nbase.strided.variancetk( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using a one-pass textbook\n    algorithm.\n"
 base.strided.variancetk.ndarray,"\nbase.strided.variancetk.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using a one-pass textbook algorithm\n    and alternative indexing semantics.\n"
 base.strided.variancewd,"\nbase.strided.variancewd( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using Welford's algorithm.\n"