Outlier Detection in PM10 Aerosols by Generalised Linear Model
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F18%3A43913796" target="_blank" >RIV/62156489:43110/18:43913796 - isvavai.cz</a>
Alternative codes found
RIV/60162694:G42__/18:00536607
Result on the web
<a href="https://doi.org/10.1063/1.5043740" target="_blank" >https://doi.org/10.1063/1.5043740</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1063/1.5043740" target="_blank" >10.1063/1.5043740</a>
Alternative languages
Result language
angličtina
Original language name
Outlier Detection in PM10 Aerosols by Generalised Linear Model
Original language description
Measurements of air pollutant concentrations often include outliers which can significantly affect further analysis and modelling. The validation of the analysed data is quite often provided manually based on subjective evaluation of the specialist which is unsatisfactory from a statistical point of view. Here the method for outlier detection in PM10 concentrations based on generalised linear model, which enables to take into account the influence of known accompanying variables, is presented. Although that the generalised linear model must be adapted to the analysed data and monitoring location the methodology is general and can be applied to concentrations of any air pollutant under the condition that the observations of accompanying variables are available.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/GA16-07089S" target="_blank" >GA16-07089S: Robust approach to testing for normality of error terms in econometric models</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the International Conference of Numerical Analysis and Applied Mathematics 2017 (ICNAAM 2017)
ISBN
978-0-7354-1690-1
ISSN
0094-243X
e-ISSN
1551-7616
Number of pages
4
Pages from-to
"nestrankovano"
Publisher name
American Institute of Physics (AIP)
Place of publication
Melville
Event location
Soluň
Event date
Sep 25, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000445105400088