Intel® Summary Statistics Library provides several opportunities for processing the datasets “contaminated” with outliers. Earlier I demonstrated how to detect “suspicious” observations in the dataset.
outliers detection
Intel® Summary Statistics Library: how fast is the algorithm for detection of outliers?
In one of my previous posts I described the scheme for detection of outliers in datasets which is important component of the Intel® Summary Statistics Library.
Intel® Summary Statistics Library: how to detect outliers in datasets?
Earlier I computed various statistical estimates like mean or variance-covariance matrix using Intel® Summary Statistics Library. In those cases I knew for sure that my datasets did not contain “bad” observations (points which do not belong to the distribution which I observed) or outliers. However, in some cases we need to deal with datasets which are contaminated with outliers.
