time-to-botec

Benchmark sampling in different programming languages
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      1 
      2 {{alias}}( W[, options] )
      3     Returns an accumulator function which incrementally performs a moving
      4     Grubbs' test for detecting outliers.
      5 
      6     Grubbs' test assumes that data is normally distributed. Accordingly, one
      7     should first verify that the data can be reasonably approximated by a normal
      8     distribution before applying the Grubbs' test.
      9 
     10     The `W` parameter defines the number of values over which to perform Grubbs'
     11     test. The minimum window size is 3.
     12 
     13     If provided a value, the accumulator function returns updated test results.
     14     If not provided a value, the accumulator function returns the current test
     15     results.
     16 
     17     Until provided `W` values, the accumulator function returns `null`.
     18 
     19     The accumulator function returns an object having the following fields:
     20 
     21     - rejected: boolean indicating whether the null hypothesis should be
     22     rejected.
     23     - alpha: significance level.
     24     - criticalValue: critical value.
     25     - statistic: test statistic.
     26     - df: degrees of freedom.
     27     - mean: sample mean.
     28     - sd: corrected sample standard deviation.
     29     - min: minimum value.
     30     - max: maximum value.
     31     - alt: alternative hypothesis.
     32     - method: method name.
     33     - print: method for pretty-printing test output.
     34 
     35     Parameters
     36     ----------
     37     W: integer
     38         Window size.
     39 
     40     options: Object (optional)
     41         Function options.
     42 
     43     options.alpha: number (optional)
     44         Significance level. Default: 0.05.
     45 
     46     options.alternative: string (optional)
     47         Alternative hypothesis. The option may be one of the following values:
     48 
     49         - 'two-sided': test whether the minimum or maximum value is an outlier.
     50         - 'min': test whether the minimum value is an outlier.
     51         - 'max': test whether the maximum value is an outlier.
     52 
     53         Default: 'two-sided'.
     54 
     55     Returns
     56     -------
     57     acc: Function
     58         Accumulator function.
     59 
     60     Examples
     61     --------
     62     > var acc = {{alias}}( 20 );
     63     > var res = acc()
     64     null
     65     > for ( var i = 0; i < 200; i++ ) {
     66     ...     res = acc( {{alias:@stdlib/random/base/normal}}( 10.0, 5.0 ) );
     67     ... };
     68     > res.print()
     69 
     70     References
     71     ----------
     72     - Grubbs, Frank E. 1950. "Sample Criteria for Testing Outlying
     73     Observations." _The Annals of Mathematical Statistics_ 21 (1). The Institute
     74     of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.
     75     - Grubbs, Frank E. 1969. "Procedures for Detecting Outlying Observations in
     76     Samples." _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/
     77     00401706.1969.10490657.
     78 
     79     See Also
     80     --------
     81