
{{alias}}( N, x, strideX, out, strideOut )
    Computes the sum of double-precision floating-point strided array elements,
    ignoring `NaN` values and using a second-order iterative Kahan–Babuška
    algorithm.

    The `N` and `stride` parameters determine which elements are accessed at
    runtime.

    Indexing is relative to the first index. To introduce an offset, use a typed
    array view.

    If `N <= 0`, the function returns a sum equal to `0.0`.

    Parameters
    ----------
    N: integer
        Number of indexed elements.

    x: Float64Array
        Input array.

    strideX: integer
        Index increment for `x`.

    out: Float64Array
        Output array.

    strideOut: integer
        Index increment for `out`.

    Returns
    -------
    out: Float64Array
        Output array whose first element is the sum and whose second element is
        the number of non-NaN elements.

    Examples
    --------
    // Standard Usage:
    > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, NaN, 2.0 ] );
    > var out = new {{alias:@stdlib/array/float64}}( 2 );
    > {{alias}}( x.length, x, 1, out, 1 )
    <Float64Array>[ 1.0, 3 ]

    // Using `N` and `stride` parameters:
    > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );
    > out = new {{alias:@stdlib/array/float64}}( 2 );
    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
    > {{alias}}( N, x, 2, out, 1 )
    <Float64Array>[ 1.0, 3 ]

    // Using view offsets:
    > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );
    > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
    > out = new {{alias:@stdlib/array/float64}}( 2 );
    > {{alias}}( N, x1, 2, out, 1 )
    <Float64Array>[ 1.0, 3 ]

{{alias}}.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )
    Computes the sum of double-precision floating-point strided array elements,
    ignoring `NaN` values and using a second-order iterative Kahan–Babuška
    algorithm and alternative indexing semantics.

    While typed array views mandate a view offset based on the underlying
    buffer, the `offset` parameter supports indexing semantics based on a
    starting index.

    Parameters
    ----------
    N: integer
        Number of indexed elements.

    x: Float64Array
        Input array.

    strideX: integer
        Index increment for `x`.

    offsetX: integer
        Starting index for `x`.

    out: Float64Array
        Output array.

    strideOut: integer
        Index increment for `out`.

    offsetOut: integer
        Starting index for `out`.

    Returns
    -------
    out: Float64Array
        Output array whose first element is the sum and whose second element is
        the number of non-NaN elements.

    Examples
    --------
    // Standard Usage:
    > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, NaN, 2.0 ] );
    > var out = new {{alias:@stdlib/array/float64}}( 2 );
    > {{alias}}.ndarray( x.length, x, 1, 0, out, 1, 0 )
    <Float64Array>[ 1.0, 3 ]

    // Using offset parameter:
    > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );
    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
    > out = new {{alias:@stdlib/array/float64}}( 2 );
    > {{alias}}.ndarray( N, x, 2, 1, out, 1, 0 )
    <Float64Array>[ 1.0, 3 ]

    See Also
    --------

