grubbs.detect: Grubbs test based identification of outliers on segments -...

In envoutliers: Methods for Identification of Outliers in Environmental Data

Description

Identification of outlier data values on individual homogeneous segments using Grubbs test. The function is called by KRDetect.outliers.changepoint and is not intended for use by regular users of the package.

Usage

grubbs.detect(x, cp.segment)

Arguments

x	a numeric vector of data.
cp.segment	an integer membership vector for individual segments.

Details

This function detects outlier observations on individual segments using Grubbs test. The function is exported for developer use only. It does not perform any checks on inputs since it is only convenience function for identification of outlier residuals.

Value

A logical vector specifing the identified outliers, TRUE means that corresponding data value from vector x is detected as outlier.

References

Grubbs F (1950). Sample criteria for testing outlying observations. The Annals of Mathematical Statistics, 21(1), 27-58.

Campulova M, Michalek J, Mikuska P, Bokal D (2018). Nonparametric algorithm for identification of outliers in environmental data. Journal of Chemometrics, 32, 453-463.

envoutliers documentation built on July 2, 2020, 3:25 a.m.