| dixon.outliers {referenceIntervals} | R Documentation |
Determines outliers using Dixon's Q Test method
Description
This determines outliers of the dataset by calculating Dixon's Q statistic and comparing it to a standardized table of statistics. This method can only determine outliers for datasets of size 3 <= n <= 30. This function requires the outliers package.
Usage
dixon.outliers(data)
Arguments
data |
A vector of data points. |
Value
Returns a list containing a vector of outliers and a vector of the cleaned data (subset).
outliers |
A vector of outliers from the data set |
subset |
A vector containing the remaining data, cleaned of outliers |
Author(s)
Daniel Finnegan
References
Statistical treatment for rejection of deviant values: critical values of Dixon's "Q" parameter and related subrange ratios at the 95 (2), pp 139-146 DOI: 10.1021/ac00002a010. Publication Date: January 1991
One-sided and Two-sided Critical Values for Dixon's Outlier Test for Sample Sizes up to n = 30. Economic Quality Control, Vol 23(2008), No. 1, 5-13.
Examples
dixon.outliers(set20)
summary(dixon.outliers(set20)$subset)