diff --git a/lib/node_modules/@stdlib/lapack/base/docs/types/index.d.ts b/lib/node_modules/@stdlib/lapack/base/docs/types/index.d.ts
index 1028d09f6908..6243df8eda00 100644
--- a/lib/node_modules/@stdlib/lapack/base/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/lapack/base/docs/types/index.d.ts
@@ -27,11 +27,14 @@ import claswp = require( '@stdlib/lapack/base/claswp' );
 import crot = require( '@stdlib/lapack/base/crot' );
 import dgetrans = require( '@stdlib/lapack/base/dge-trans' );
 import dgttrf = require( '@stdlib/lapack/base/dgttrf' );
+import disnan = require( '@stdlib/lapack/base/disnan' );
 import dlacpy = require( '@stdlib/lapack/base/dlacpy' );
 import dladiv = require( '@stdlib/lapack/base/dladiv' );
+import dlaisnan = require( '@stdlib/lapack/base/dlaisnan' );
 import dlamch = require( '@stdlib/lapack/base/dlamch' );
 import dlapy2 = require( '@stdlib/lapack/base/dlapy2' );
 import dlapy3 = require( '@stdlib/lapack/base/dlapy3' );
+import dlarf = require( '@stdlib/lapack/base/dlarf' );
 import dlarf1f = require( '@stdlib/lapack/base/dlarf1f' );
 import dlaset = require( '@stdlib/lapack/base/dlaset' );
 import dlassq = require( '@stdlib/lapack/base/dlassq' );
@@ -311,6 +314,22 @@ interface Namespace {
 	*/
 	dgttrf: typeof dgttrf;
 
+	/**
+	* Tests whether a double-precision floating-point number is NaN.
+	*
+	* @param x - input value
+	* @returns boolean indicating whether an input value is NaN
+	*
+	* @example
+	* var bool = ns.disnan( NaN );
+	* // returns true
+	*
+	* @example
+	* var bool = ns.disnan( 5.0 );
+	* // returns false
+	*/
+	disnan: typeof disnan;
+
 	/**
 	* Copies all or part of a matrix `A` to another matrix `B`.
 	*
@@ -377,6 +396,27 @@ interface Namespace {
 	*/
 	dladiv: typeof dladiv;
 
+	/**
+	* LAPACK auxiliary routine to test input for NaN by comparing two double-precision floating-point arguments for inequality.
+	*
+	* @param din1 - first input number
+	* @param din2 - second input number
+	* @returns boolean indicating whether the arguments are unequal
+	*
+	* @example
+	* var bool = ns.dlaisnan( NaN, NaN );
+	* // returns true
+	*
+	* @example
+	* var bool = ns.dlaisnan( NaN, 5.0 );
+	* // returns true
+	*
+	* @example
+	* var bool = ns.dlaisnan( 5.0, 5.0 );
+	* // returns false
+	*/
+	dlaisnan: typeof dlaisnan;
+
 	/**
 	* Determines double-precision floating-point machine parameters.
 	*
@@ -445,6 +485,57 @@ interface Namespace {
 	*/
 	dlapy3: typeof dlapy3;
 
+	/**
+	* Applies a real elementary reflector `H = I - tau * v * v^T` to a real M by N matrix `C`.
+	*
+	* ## Notes
+	*
+	* -   If `side = 'left'`,
+	*
+	*     -   `work` should have `N` indexed elements.
+	*     -   `V` should have `1 + (M-1) * abs(strideV)` indexed elements.
+	*     -   `C` is overwritten by `H * C`.
+	*
+	* -   If `side = 'right'`,
+	*
+	*     -   `work` should have `M` indexed elements.
+	*     -   `V` should have `1 + (N-1) * abs(strideV)` indexed elements.
+	*     -   `C` is overwritten by `C * H`.
+	*
+	* @param order - storage layout
+	* @param side - specifies the side of multiplication with `C`
+	* @param M - number of rows in `C`
+	* @param N - number of columns in `C`
+	* @param V - the vector `v`
+	* @param strideV - stride length for `V`
+	* @param tau - scalar constant
+	* @param C - input matrix
+	* @param ldc - stride of the first dimension of `C` (a.k.a., leading dimension of the matrix `C`)
+	* @param work - workspace array
+	* @returns `C * H` or `H * C`
+	*
+	* @example
+	* var Float64Array = require( '@stdlib/array/float64' );
+	*
+	* var C = new Float64Array( [ 1.0, 5.0, 9.0, 2.0, 6.0, 10.0, 3.0, 7.0, 11.0, 4.0, 8.0, 12.0 ] );
+	* var V = new Float64Array( [ 0.5, 0.5, 0.5, 0.5 ] );
+	* var work = new Float64Array( 3 );
+	*
+	* var out = ns.dlarf( 'row-major', 'left', 4, 3, V, 1, 1.0, C, 3, work );
+	* // returns <Float64Array>[ -1.5, -1.5, -1.5, -0.5, -0.5, -0.5, 0.5, 0.5, 0.5, 1.5, 1.5, 1.5 ]
+	*
+	* @example
+	* var Float64Array = require( '@stdlib/array/float64' );
+	*
+	* var C = new Float64Array( [ 1.0, 5.0, 9.0, 2.0, 6.0, 10.0, 3.0, 7.0, 11.0, 4.0, 8.0, 12.0 ] );
+	* var V = new Float64Array( [ 0.5, 0.5, 0.5, 0.5 ] );
+	* var work = new Float64Array( 3 );
+	*
+	* var out = ns.dlarf.ndarray( 'left', 4, 3, V, 1, 0, 1.0, C, 3, 1, 0, work, 1, 0 );
+	* // returns <Float64Array>[ -1.5, -1.5, -1.5, -0.5, -0.5, -0.5, 0.5, 0.5, 0.5, 1.5, 1.5, 1.5 ]
+	*/
+	dlarf: typeof dlarf;
+
 	/**
 	* Applies a real elementary reflector `H = I - tau * v * v^T` to a real M by N matrix `C`.
 	*