chebyshev.inequality.detect {envoutliers}

Chebyshev inequality based identification of outliers on segments - Only intended for developer use

Description

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

Usage

chebyshev.inequality.detect(x, cp.segment, L.default)

Arguments

x

a numeric vector of data.

cp.segment

an integer membership vector for individual segments.

L.default

a numeric value of L parameter determining the criterion for outlier detection: the limits for outlier observations on individual segments are set as +/- L * sample standard deviation of data on the corresponding segment If L.default = NULL, its value on individual segments is estimated using Algorithm A1 (Campulova et al., 2018).

Details

This function detects outlier observations on individual segments using Chebyshev inequality. 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 list is returned with elements:

L

a numeric vector of L parameters used for outlier identification on individual segments

outlier

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

References

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