referenceIntervals (version 1.2.0)

dixon.outliers: 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

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

# NOT RUN {
  
dixon.outliers(set20)
summary(dixon.outliers(set20)$subset)

# }

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