
{{alias}}( arrays )
    Computes the mean and standard deviation of a one-dimensional double-
    precision floating-point ndarray.

    If provided an empty ndarray, the function returns `NaN` values.

    Parameters
    ----------
    arrays: ArrayLikeObject<ndarray>
        Array-like object containing the following ndarrays:

        - a one-dimensional input ndarray.
        - a one-dimensional output ndarray to store the mean and standard
        deviation.
        - a zero-dimensional ndarray specifying the degrees of freedom
        adjustment. Providing a non-zero degrees of freedom adjustment has the
        effect of adjusting the divisor during the calculation of the standard
        deviation according to `N-c` where `N` is the number of elements in the
        input ndarray and `c` corresponds to the provided degrees of freedom
        adjustment. When computing the standard deviation of a population,
        setting this parameter to `0` is the standard choice (i.e., the provided
        array contains data constituting an entire population). When computing
        the corrected sample standard deviation, setting this parameter to `1`
        is the standard choice (i.e., the provided array contains data sampled
        from a larger population; this is commonly referred to as Bessel's
        correction).

    Returns
    -------
    out: ndarray
        Output ndarray.

    Examples
    --------
    > var x = new {{alias:@stdlib/ndarray/vector/float64}}( [ 2.0, 1.0, 2.0, -2.0 ] );
    > var out = new {{alias:@stdlib/ndarray/vector/float64}}( 2 );
    > var opts = { 'dtype': 'float64' };
    > var correction = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts );
    > {{alias}}( [ x, out, correction ] );
    > out
    <ndarray>[ ~0.75, ~1.8930 ]

    See Also
    --------

