{{alias}}( x[, ...y[, options]] )
    Computes Levene's test for equal variances.

    Parameters
    ----------
    x: Array<number>
        Measured values.

    y: ...Array<number> (optional)
        Measured values.

    options: Object (optional)
        Options.

    options.alpha: number (optional)
        Number in the interval `[0,1]` giving the significance level of the
        hypothesis test. Default: `0.05`.

    options.groups: Array (optional)
        Array of group indicators.

    Returns
    -------
    out: Object
        Test result object.

    out.alpha: number
        Significance level.

    out.rejected: boolean
        Test decision.

    out.pValue: number
        p-value of the test.

    out.statistic: number
        Value of test statistic.

    out.method: string
        Name of test.

    out.df: Array
        Degrees of freedom.

    out.print: Function
        Function to print formatted output.

    Examples
    --------
    // Data from Hollander & Wolfe (1973), p. 116:
    > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];
    > var y = [ 3.8, 2.7, 4.0, 2.4 ];
    > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];

    > var out = {{alias}}( x, y, z )

    > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,
    ...     3.8, 2.7, 4.0, 2.4,
    ...     2.8, 3.4, 3.7, 2.2, 2.0
    ... ];
    > var groups = [
    ...     'a', 'a', 'a', 'a', 'a',
    ...     'b', 'b', 'b', 'b',
    ...     'c', 'c', 'c', 'c', 'c'
    ... ];
    > out = {{alias}}( arr, { 'groups': groups } )

    See Also
    --------