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ČAMPULOVÁ, M. ČAMPULA, R. HOLEŠOVSKÝ, J.
Originální název
An R package for identification of outliers in environmental time series data
Typ
článek v časopise ve Web of Science, Jimp
Jazyk
angličtina
Originální abstrakt
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.
Klíčová slova
Outlier; Data validation; Kernel regression; Environmental data; R package
Autoři
ČAMPULOVÁ, M.; ČAMPULA, R.; HOLEŠOVSKÝ, J.
Vydáno
17. 8. 2022
Nakladatel
Elsevier
Místo
Amsterdam
ISSN
1364-8152
Periodikum
ENVIRONMENTAL MODELLING & SOFTWARE
Ročník
155
Číslo
1
Stát
Spojené království Velké Británie a Severního Irska
Strany od
Strany do
18
Strany počet
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" }