CRAN/E | envoutliers

envoutliers

Methods for Identification of Outliers in Environmental Data

Installation

About

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).

Citation envoutliers citation info

Key Metrics

Version 1.1.0
Published 2020-05-07 1451 days ago
Needs compilation? no
License GPL-2
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Maintainer

Maintainer

Martina Campulova

martina.campulova@mendelu.cz

Authors

Martina Campulova

cre

Martina Campulova

aut

Roman Campula

ctb

Material

NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

envoutliers archive

Imports

MASS
car
changepoint
ecp
graphics
ismev
lokern
robustbase
stats

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