
{{alias}}( arrays )
    Computes the standard deviation of a one-dimensional double-precision
    floating-point ndarray, ignoring `NaN` values.

    If provided an empty one-dimensional ndarray, the function returns `NaN`.

    If `N - c` is less than or equal to `0` (where `N` corresponds to the number
    of non-NaN elements in the input ndarray and `c` corresponds to the provided
    degrees of freedom adjustment), the function returns `NaN`.

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

        - a one-dimensional input ndarray.
        - 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 non-NaN 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: number
        The standard deviation.

    Examples
    --------
    // Create input ndarray:
    > var x = new {{alias:@stdlib/ndarray/vector/float64}}( [ 1.0, -2.0, NaN, 2.0 ] );

    // Create correction ndarray:
    > var opts = { 'dtype': 'float64' };
    > var correction = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts );

    // Compute the standard deviation:
    > {{alias}}( [ x, correction ] )
    ~2.0817

    See Also
    --------

