grubbs.detect

an integer membership vector for individual segments.

cp.segment

Identification of outlier data values on individual homogeneous segments using Grubbs test.
The function is called by <code><a rd-options="" href="/link/KRDetect.outliers.changepoint?package=envoutliers&version=1.1.0" data-mini-rdoc="envoutliers::KRDetect.outliers.changepoint">KRDetect.outliers.changepoint</a></code> and is not intended for use by regular users of the package.

Three semi-parametric methods for detection of outliers in environmental data based on kernel regression and subsequent analysis of smoothing residuals. The first method (Campulova, Michalek, Mikuska and Bokal (2018) <DOI: 10.1002/cem.2997>) analyzes the residuals using changepoint analysis, the second method is based on control charts (Campulova, Veselik and Michalek (2017) <DOI: 10.1016/j.apr.2017.01.004>) and the third method (Holesovsky, Campulova and Michalek (2018) <DOI: 10.1016/j.apr.2017.06.005>) analyzes the residuals using extreme value theory (Holesovsky, Campulova and Michalek (2018) <DOI: 10.1016/j.apr.2017.06.005>).

Martina Campulova

envoutliers

Methods for Identification of Outliers in Environmental Data

Roman Campula

grubbs.detect function

Identification of outlier data values on individual homogeneous segments using Grubbs test.
The function is called by <code><a rd-options='' href='KRDetect.outliers.changepoint'>KRDetect.outliers.changepoint</a></code> and is not intended for use by regular users of the package.

grubbs.detect: Grubbs test based identification of outliers on segments - Only intended for developer use

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