Outlier Identification of Concentrations of Pollutants in Environmental Data Using Modern Statistical Methods

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25510%2F20%3A39916008" target="_blank" >RIV/00216275:25510/20:39916008 - isvavai.cz</a>
Alternative codes found
RIV/60162694:G42__/20:00555510
Result on the web
<a href="http://www.pjoes.com/Outlier-Identification-of-Concentrations-nof-Pollutants-in-Environmental-Data-Using,112620,0,2.html" target="_blank" >http://www.pjoes.com/Outlier-Identification-of-Concentrations-nof-Pollutants-in-Environmental-Data-Using,112620,0,2.html</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.15244/pjoes/112620" target="_blank" >10.15244/pjoes/112620</a>

Result language
angličtina
Original language name
Outlier Identification of Concentrations of Pollutants in Environmental Data Using Modern Statistical Methods
Original language description
The article is focused on identification of outlier measurements in environmental data which may significantly affect the future results of the analysis and interpretation of results. For this reason, their identification forms an integral part of data analysis. The aim of this article is to perform statistical analysis that automatically identifies segments of outlier measurements. The results were demonstrated on real concentration data. The methodological procedure was used to evaluate particulate matter of the PM10 fraction size from two monitoring stations located in Brno, Czech Republic.
Czech name
—
Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10511 - Environmental sciences (social aspects to be 5.7)

Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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