Publication result detail

An R package for identification of outliers in environmental time series data

ČAMPULOVÁ, M.; ČAMPULA, R.; HOLEŠOVSKÝ, J.

Original Title

An R package for identification of outliers in environmental time series data

English Title

An R package for identification of outliers in environmental time series data

Type

WoS Article

Original Abstract

Environmental data often include outliers that may significantly affect further modelling and data analysis. Although a number of outlier detection methods have been proposed, their use is usually complicated by the assumption of the distribution or model of the analyzed data. However, environmental variables are quite often influenced by many different factors and their distribution is difficult to estimate. The envoutliers package has been developed to provide users with a choice of recently presented, semi-parametric outlier detection methods that do not impose requirements on the distribution of the original data. This paper briefly describes the methodology as well as its implementation in the package. The application is illustrated on real data examples.

English abstract

Environmental data often include outliers that may significantly affect further modelling and data analysis. Although a number of outlier detection methods have been proposed, their use is usually complicated by the assumption of the distribution or model of the analyzed data. However, environmental variables are quite often influenced by many different factors and their distribution is difficult to estimate. The envoutliers package has been developed to provide users with a choice of recently presented, semi-parametric outlier detection methods that do not impose requirements on the distribution of the original data. This paper briefly describes the methodology as well as its implementation in the package. The application is illustrated on real data examples.

Keywords

Outlier; Data validation; Kernel regression; Environmental data; R package

Key words in English

Outlier; Data validation; Kernel regression; Environmental data; R package

Authors

ČAMPULOVÁ, M.; ČAMPULA, R.; HOLEŠOVSKÝ, J.

RIV year

2023

Released

17.08.2022

Publisher

Elsevier

Location

Amsterdam

ISBN

1364-8152

Periodical

ENVIRONMENTAL MODELLING & SOFTWARE

Volume

155

Number

1

State

United Kingdom of Great Britain and Northern Ireland

Pages from

1

Pages to

18

Pages count

18

URL

https://pdf.sciencedirectassets.com/271872/1-s2.0-S1364815222X00066/1-s2.0-S1364815222001414/main.pdf?X-Amz-Security-Token=IQoJb3JpZ2luX2VjEMv%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEaCXVzLWVhc3QtMSJIMEYCIQCABrXH%2BDuWf%2B%2B0OCEjAGscLGJgzmHXUKShx53gqrtk%2FAIhAPdrGiB%2F2IKift3R96EFSLR%2BQqZs3yZquo0dGlmddqPYKtsECNT%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEQBBoMMDU5MDAzNTQ2ODY1IgzgXROrZoM9BjdM%2FDwqrwTm%2FTbuH1A9xg4Q7K%2FY7amewXMUHfD%2BGVQNn8EmXUwUml4hSRfYrrf94bL84IpNiNPOs0RmANltVk4hl5%2BlO1yOXvNf%2BJwVS7ESdB4eusSvrD%2ByhGet4CG

BibTex

@article{BUT178243,
  author="Martina {Čampulová} and Roman {Čampula} and Jan {Holešovský}",
  title="An R package for identification of outliers in environmental time series data",
  journal="ENVIRONMENTAL MODELLING & SOFTWARE",
  year="2022",
  volume="155",
  number="1",
  pages="1--18",
  doi="10.1016/j.envsoft.2022.105435",
  issn="1364-8152",
  url="https://pdf.sciencedirectassets.com/271872/1-s2.0-S1364815222X00066/1-s2.0-S1364815222001414/main.pdf?X-Amz-Security-Token=IQoJb3JpZ2luX2VjEMv%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEaCXVzLWVhc3QtMSJIMEYCIQCABrXH%2BDuWf%2B%2B0OCEjAGscLGJgzmHXUKShx53gqrtk%2FAIhAPdrGiB%2F2IKift3R96EFSLR%2BQqZs3yZquo0dGlmddqPYKtsECNT%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEQBBoMMDU5MDAzNTQ2ODY1IgzgXROrZoM9BjdM%2FDwqrwTm%2FTbuH1A9xg4Q7K%2FY7amewXMUHfD%2BGVQNn8EmXUwUml4hSRfYrrf94bL84IpNiNPOs0RmANltVk4hl5%2BlO1yOXvNf%2BJwVS7ESdB4eusSvrD%2ByhGet4CG"
}