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Monotonic regression for assessment of trends in environmental quality data
Linköping University, Faculty of Arts and Sciences. Linköping University, Department of Mathematics, Statistics.
Linköping University, Faculty of Arts and Sciences. Linköping University, Department of Mathematics, Statistics.
Linköping University, The Institute of Technology. Linköping University, Department of Mathematics, Optimization .ORCID iD: 0000-0003-1836-4200
2004 (English)In: European Congress on Computational Methods in Applied Sciences and Engineering ECCOMAS / [ed] P. Neittaanmäki, T. Rossi, K. Majava and O. Pironneau, Jyväskylä: University of Jyväskylä, Department of Mathematical Information Technology , 2004, 1-12 p.Conference paper, Published paper (Refereed)
Abstract [en]

Monotonic regression is a non-parametric method that is designed especially for applications in which the expected value of a response variable increases or decreases in one or more explanatory variables. Here, we show how the recently developed generalised pool-adjacent-violators (GPAV) algorithm can greatly facilitate the assessment of trends in time series of environmental quality data. In particular, we present new methods for simultaneous extraction of a monotonic trend and seasonal components, and for normalisation of environmental quality data that are influenced by random variation in weather conditions or other forms of natural variability. The general aim of normalisation is to clarify the human impact on the environment by suppressing irrelevant variation in the collected data. Our method is designed for applications that satisfy the following conditions: (i) the response variable under consideration is a monotonic function of one or more covariates; (ii) the anthropogenic temporal trend is either increasing or decreasing; (iii) the seasonal variation over a year can be defined by one increasing and one decreasing function. Theoretical descriptions of our methodology are accompanied by examples of trend assessments of water quality data and normalisation of the mercury concentration in cod muscle in relation to the length of the analysed fish.

Place, publisher, year, edition, pages
Jyväskylä: University of Jyväskylä, Department of Mathematical Information Technology , 2004. 1-12 p.
Keyword [en]
Monotonic regression, Response surface, Time series decomposition, Normalisation
National Category
Computational Mathematics Probability Theory and Statistics Environmental Management
Identifiers
URN: urn:nbn:se:liu:diva-24328Local ID: 3956ISBN: 951-39-1868-8 (print)OAI: oai:DiVA.org:liu-24328DiVA: diva2:244646
Conference
The 4th European Congress of Computational Methods in Applied Science and Engineering "ECCOMAS 2004"
Available from: 2009-10-07 Created: 2009-10-07 Last updated: 2015-06-02

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Hussian, MohamedGrimvall, AndersBurdakov, Oleg

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