On Ecological Aspects of Dynamics for Zero Slope Regression for Water Pollution in Chile

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F19%3A00504430" target="_blank" >RIV/67985807:_____/19:00504430 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1080/07362994.2019.1592692" target="_blank" >http://dx.doi.org/10.1080/07362994.2019.1592692</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/07362994.2019.1592692" target="_blank" >10.1080/07362994.2019.1592692</a>

Result language
angličtina
Original language name
On Ecological Aspects of Dynamics for Zero Slope Regression for Water Pollution in Chile
Original language description
Zero slope regression is an important problem in chemometrics, ranging from challenges of intercept-bias and slope ‘corrections’ in spectrometry, up to analysis of administrative data on chemical pollution in water in the region of Arica and Parinacota. Such issue is really complex and it integrates problems of optimal design, symmetry of errors, stabilization of the variability of estimators, dynamical system for errors up to an administrative data challenges. In this article we introduce a realistic approach to zero slope regression problem from dynamical point of view. Linear regression is a widely used approach for data fitting under assumption of normally distributed residuals. Many times non-normal residuals are observed and also theoretically justified. Our solution to such problem uses the recently introduced inference function called score function of distribution. As a minimization criterion, the minimum information of residuals criterion is used. The score regression appears to be a direct generalization of the least-squares regression for an arbitrary known (believed) distribution of residuals. The score estimation is also distribution sensitive version of M-estimation. The capability of the method is demonstrated by water pollution data examples.
Czech name
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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
—
OECD FORD branch
10103 - Statistics and probability

Project
<a href="/en/project/EF16_013%2F0001787" target="_blank" >EF16_013/0001787: Collaboration on Fermilab experiments</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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