
{{alias}}( [options] )
    Returns an accumulator function which incrementally performs Grubbs' test
    for detecting outliers.

    Grubbs' test assumes that data is normally distributed. Accordingly, one
    should first verify that the data can be reasonably approximated by a normal
    distribution before applying the Grubbs' test.

    If provided a value, the accumulator function returns updated test results.
    If not provided a value, the accumulator function returns the current test
    results.

    If provided `NaN` or a value which, when used in computations, results in
    `NaN`, the test statistic is `NaN` for all future invocations.

    The accumulator must be provided *at least* three data points before
    performing Grubbs' test. Until at least three data points are provided, the
    accumulator returns `null`.

    The accumulator function returns an object having the following fields:

    - rejected: boolean indicating whether the null hypothesis should be
    rejected.
    - alpha: significance level.
    - criticalValue: critical value.
    - statistic: test statistic.
    - df: degrees of freedom.
    - mean: sample mean.
    - sd: corrected sample standard deviation.
    - min: minimum value.
    - max: maximum value.
    - alt: alternative hypothesis.
    - method: method name.
    - print: method for pretty-printing test output.

    Parameters
    ----------
    options: Object (optional)
        Function options.

    options.alpha: number (optional)
        Significance level. Default: 0.05.

    options.alternative: string (optional)
        Alternative hypothesis. The option may be one of the following values:

        - 'two-sided': test whether the minimum or maximum value is an outlier.
        - 'min': test whether the minimum value is an outlier.
        - 'max': test whether the maximum value is an outlier.

        Default: 'two-sided'.

    options.init: integer (optional)
        Number of data points the accumulator should use to compute initial
        statistics *before* testing for an outlier. Until the accumulator is
        provided the number of data points specified by this option, the
        accumulator returns `null`. Default: 100.

    Returns
    -------
    acc: Function
        Accumulator function.

    Examples
    --------
    > var acc = {{alias}}();
    > var res = acc()
    null
    > for ( var i = 0; i < 200; i++ ) {
    ...     res = acc( {{alias:@stdlib/random/base/normal}}( 10.0, 5.0 ) );
    ... };
    > res.print()

    References
    ----------
    - Grubbs, Frank E. 1950. "Sample Criteria for Testing Outlying
    Observations." _The Annals of Mathematical Statistics_ 21 (1). The Institute
    of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.
    - Grubbs, Frank E. 1969. "Procedures for Detecting Outlying Observations in
    Samples." _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/
    00401706.1969.10490657.

    See Also
    --------

