diff --git a/docs/migration-guides/numpy/README.md b/docs/migration-guides/numpy/README.md
index 827f7f5591d2..d9663913d22c 100644
--- a/docs/migration-guides/numpy/README.md
+++ b/docs/migration-guides/numpy/README.md
@@ -48,7 +48,7 @@ limitations under the License.
 | Filter an array according to a predicate function | `x[np.vectorize(predicate)(x)]` | [`filter(x, predicate)`][@stdlib/ndarray/filter] |
 | Find the index of the first element which equals a specified value | `np.argmax(x == v, axis=dim)` | [`indexOf(x, v, {dim: dim})`][@stdlib/blas/ext/index-of] |
 | Find the index of the last element which equals a specified value | `x.shape[dim]-1-np.argmax(np.flip(x, axis=dim) == v, axis=dim)` | [`lastIndexOf(x, v, {dim: dim})`][@stdlib/blas/ext/last-index-of] |
-| Flatten an array to a desired depth | `np.reshape(x, newshape)`] | [`flatten(x, {depth: depth})`][@stdlib/ndarray/flatten] |
+| Flatten an array to a desired depth | `np.reshape(x, newshape)` | [`flatten(x, {depth: depth})`][@stdlib/ndarray/flatten] |
 | Flatten an array starting from a specific dimension | `np.reshape(x, x.shape[:dim] + (-1,))` | [`flattenFrom(x, dim)`][@stdlib/ndarray/flatten-from] |
 | Prepend a specified number of singleton dimensions | `np.reshape(x, (1,)*n + x.shape)` | [`prependSingletonDimensions(x, n)`][@stdlib/ndarray/prepend-singleton-dimensions] |
 | Prepend a zero-filled array of the same shape along a specified dimension | `np.concat((np.zeros_like(x), x), axis=dim)` | [`concat([zerosLike(x), x], {dim: dim})`][@stdlib/ndarray/concat] |
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/docs/types/index.d.ts
index 40630a2f9ee8..d3374d58a5ff 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/docs/types/index.d.ts
@@ -173,14 +173,10 @@ interface Namespace {
 	* @returns second input ndarray
 	*
 	* @example
-	* var Float64Array = require( '@stdlib/array/float64' );
-	* var ndarray = require( '@stdlib/ndarray/base/ctor' );
-	*
-	* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
-	* var x = new ndarray( 'float64', xbuf, [ 5 ], [ 1 ], 0, 'row-major' );
+	* var Float64Vector = require( '@stdlib/ndarray/vector/float64' );
 	*
-	* var ybuf = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );
-	* var y = new ndarray( 'float64', ybuf, [ 5 ], [ 1 ], 0, 'row-major' );
+	* var x = new Float64Vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
+	* var y = new Float64Vector( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );
 	*
 	* var z = ns.dswap( [ x, y ] );
 	* // x => <ndarray>[ 6.0, 7.0, 8.0, 9.0, 10.0 ]
diff --git a/lib/node_modules/@stdlib/types/index.d.ts b/lib/node_modules/@stdlib/types/index.d.ts
index 229689153653..65c1d58576d0 100644
--- a/lib/node_modules/@stdlib/types/index.d.ts
+++ b/lib/node_modules/@stdlib/types/index.d.ts
@@ -670,7 +670,7 @@ declare module '@stdlib/types/array' {
 	* @example
 	* const buf = new Float16Array( 8 );
 	*
-	* const z: Complex64Array = {
+	* const z: Complex32Array = {
 	*     'byteLength': 16,
 	*     'byteOffset': 0,
 	*     'BYTES_PER_ELEMENT': 2,