
Criterion.Analysis  Portability  GHC  Stability  experimental  Maintainer  bos@serpentine.com 



Description 
Analysis code for benchmarks.


Synopsis 



Documentation 


Outliers from sample data, calculated using the boxplot
technique.
 Constructors  Outliers   samplesSeen :: !Int64   lowSevere :: !Int64  More than 3 times the IQR below the first quartile.
 lowMild :: !Int64  Between 1.5 and 3 times the IQR below the first quartile.
 highMild :: !Int64  Between 1.5 and 3 times the IQR above the third quartile.
 highSevere :: !Int64  More than 3 times the IQR above the third quartile.


 Instances  



A description of the extent to which outliers in the sample data
affect the sample mean and standard deviation.
 Constructors  Unaffected  Less than 1% effect.
 Slight  Between 1% and 10%.
 Moderate  Between 10% and 50%.
 Severe  Above 50% (i.e. measurements
are useless).

 Instances  



:: Sample   > Int  Number of iterations used to
compute the sample.
 > ConfigM Double   Display the mean of a Sample, and characterise the outliers
present in the sample.




Count the total number of outliers in a sample.



Classify outliers in a data set, using the boxplot technique.



Display a report of the Outliers present in a Sample.



:: Estimate  Bootstrap estimate of sample mean.
 > Estimate  Bootstrap estimate of sample
standard deviation.
 > Double  Number of original iterations.
 > (OutlierVariance, Double)   Compute the extent to which outliers in the sample data affect
the sample mean and standard deviation.



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