feat: update stats/base/ndarray TypeScript declarations

lib/node_modules/@stdlib/stats/base/ndarray/docs/types/index.d.ts

@@ -71,6 +71,7 @@ import dnanrangeabs = require( '@stdlib/stats/base/ndarray/dnanrangeabs' );
 import dnanstdev = require( '@stdlib/stats/base/ndarray/dnanstdev' );
 import dnanstdevch = require( '@stdlib/stats/base/ndarray/dnanstdevch' );
 import dnanstdevpn = require( '@stdlib/stats/base/ndarray/dnanstdevpn' );
+import dnanvariance = require( '@stdlib/stats/base/ndarray/dnanvariance' );
 import drange = require( '@stdlib/stats/base/ndarray/drange' );
 import drangeabs = require( '@stdlib/stats/base/ndarray/drangeabs' );
 import dstdev = require( '@stdlib/stats/base/ndarray/dstdev' );
@@ -129,6 +130,9 @@ import nanmskmin = require( '@stdlib/stats/base/ndarray/nanmskmin' );
 import nanmskrange = require( '@stdlib/stats/base/ndarray/nanmskrange' );
 import nanrange = require( '@stdlib/stats/base/ndarray/nanrange' );
 import nanrangeBy = require( '@stdlib/stats/base/ndarray/nanrange-by' );
+import nanvariance = require( '@stdlib/stats/base/ndarray/nanvariance' );
+import nanvariancech = require( '@stdlib/stats/base/ndarray/nanvariancech' );
+import nanvariancepn = require( '@stdlib/stats/base/ndarray/nanvariancepn' );
 import range = require( '@stdlib/stats/base/ndarray/range' );
 import rangeBy = require( '@stdlib/stats/base/ndarray/range-by' );
 import rangeabs = require( '@stdlib/stats/base/ndarray/rangeabs' );
@@ -1452,6 +1456,35 @@ interface Namespace {
 	*/
 	dnanstdevpn: typeof dnanstdevpn;
 
+	/**
+	* Computes the variance of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.
+	*
+	* ## Notes
+	*
+	* -   The function expects the following ndarrays:
+	*
+	*     -   a one-dimensional input ndarray.
+	*     -   a zero-dimensional ndarray specifying the degrees of freedom adjustment.
+	*
+	* @param arrays - array-like object containing ndarrays
+	* @returns variance
+	*
+	* @example
+	* var Float64Vector = require( '@stdlib/ndarray/vector/float64' );
+	* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+	*
+	* var opts = {
+	*     'dtype': 'float64'
+	* };
+	*
+	* var x = new Float64Vector( [ 1.0, -2.0, NaN, 2.0 ] );
+	* var correction = scalar2ndarray( 1.0, opts );
+	*
+	* var v = ns.dnanvariance( [ x, correction ] );
+	* // returns ~4.3333
+	*/
+	dnanvariance: typeof dnanvariance;
+
 	/**
 	* Computes the range of a one-dimensional double-precision floating-point ndarray.
 	*
@@ -2948,6 +2981,87 @@ interface Namespace {
 	*/
 	nanrangeBy: typeof nanrangeBy;
 
+	/**
+	* Computes the variance of a one-dimensional ndarray, ignoring `NaN` values.
+	*
+	* ## Notes
+	*
+	* -   The function expects the following ndarrays:
+	*
+	*     -   a one-dimensional input ndarray.
+	*     -   a zero-dimensional ndarray specifying the degrees of freedom adjustment.
+	*
+	* @param arrays - array-like object containing ndarrays
+	* @returns variance
+	*
+	* @example
+	* var vector = require( '@stdlib/ndarray/vector/ctor' );
+	* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+	*
+	* var x = vector( [ 1.0, -2.0, 2.0, NaN ], 'generic' );
+	* var correction = scalar2ndarray( 1.0, {
+	*     'dtype': 'generic'
+	* });
+	*
+	* var v = ns.nanvariance( [ x, correction ] );
+	* // returns ~4.3333
+	*/
+	nanvariance: typeof nanvariance;
+
+	/**
+	* Computes the variance of a one-dimensional ndarray, ignoring `NaN` values and using a one-pass trial mean algorithm.
+	*
+	* ## Notes
+	*
+	* -   The function expects the following ndarrays:
+	*
+	*     -   a one-dimensional input ndarray.
+	*     -   a zero-dimensional ndarray specifying the degrees of freedom adjustment.
+	*
+	* @param arrays - array-like object containing ndarrays
+	* @returns variance
+	*
+	* @example
+	* var vector = require( '@stdlib/ndarray/vector/ctor' );
+	* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+	*
+	* var x = vector( [ 1.0, -2.0, 2.0, NaN ], 'generic' );
+	* var correction = scalar2ndarray( 1.0, {
+	*     'dtype': 'generic'
+	* });
+	*
+	* var v = ns.nanvariancech( [ x, correction ] );
+	* // returns ~4.3333
+	*/
+	nanvariancech: typeof nanvariancech;
+
+	/**
+	* Computes the variance of a one-dimensional ndarray, ignoring `NaN` values and using a two-pass algorithm.
+	*
+	* ## Notes
+	*
+	* -   The function expects the following ndarrays:
+	*
+	*     -   a one-dimensional input ndarray.
+	*     -   a zero-dimensional ndarray specifying the degrees of freedom adjustment.
+	*
+	* @param arrays - array-like object containing ndarrays
+	* @returns variance
+	*
+	* @example
+	* var vector = require( '@stdlib/ndarray/vector/ctor' );
+	* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+	*
+	* var x = vector( [ 1.0, -2.0, 2.0, NaN ], 'generic' );
+	* var correction = scalar2ndarray( 1.0, {
+	*     'dtype': 'generic'
+	* });
+	*
+	* var v = ns.nanvariancepn( [ x, correction ] );
+	* // returns ~4.3333
+	*/
+	nanvariancepn: typeof nanvariancepn;
+
 	/**
 	* Computes the range of a one-dimensional ndarray.
 	*