Statistical Methods for the Qualitative Assessment of Dynamic Models with Time Delay (R Package qualV)

Results of ecological models differ, to some extent, more from measured data than from empirical knowledge. Existing techniques for validation based on quantitative assessments sometimes cause an underestimation of the performance of models due to time shifts, accelerations and delays or systematic...

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Main Authors: Stefanie Jachner, K. Gerald van den Boogaart, Thomas Petzoldt
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2007-06-01
Series:Journal of Statistical Software
Subjects:
R
Online Access:http://www.jstatsoft.org/v22/i08/paper
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spelling doaj-717891947c444d3497474168cc647c842020-11-24T23:02:33ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602007-06-01228Statistical Methods for the Qualitative Assessment of Dynamic Models with Time Delay (R Package qualV)Stefanie JachnerK. Gerald van den BoogaartThomas PetzoldtResults of ecological models differ, to some extent, more from measured data than from empirical knowledge. Existing techniques for validation based on quantitative assessments sometimes cause an underestimation of the performance of models due to time shifts, accelerations and delays or systematic differences between measurement and simulation. However, for the application of such models it is often more important to reproduce essential patterns instead of seemingly exact numerical values. This paper presents techniques to identify patterns and numerical methods to measure the consistency of patterns between observations and model results. An orthogonal set of deviance measures for absolute, relative and ordinal scale was compiled to provide informations about the type of difference. Furthermore, two different approaches accounting for time shifts were presented. The first one transforms the time to take time delays and speed differences into account. The second one describes known qualitative criteria dividing time series into interval units in accordance to their main features. The methods differ in their basic concepts and in the form of the resulting criteria. Both approaches and the deviance measures discussed are implemented in an R package. All methods are demonstrated by means of water quality measurements and simulation data. The proposed quality criteria allow to recognize systematic differences and time shifts between time series and to conclude about the quantitative and qualitative similarity of patterns.http://www.jstatsoft.org/v22/i08/paperecological modelingqualitative validation criteriatime shiftR
collection DOAJ
language English
format Article
sources DOAJ
author Stefanie Jachner
K. Gerald van den Boogaart
Thomas Petzoldt
spellingShingle Stefanie Jachner
K. Gerald van den Boogaart
Thomas Petzoldt
Statistical Methods for the Qualitative Assessment of Dynamic Models with Time Delay (R Package qualV)
Journal of Statistical Software
ecological modeling
qualitative validation criteria
time shift
R
author_facet Stefanie Jachner
K. Gerald van den Boogaart
Thomas Petzoldt
author_sort Stefanie Jachner
title Statistical Methods for the Qualitative Assessment of Dynamic Models with Time Delay (R Package qualV)
title_short Statistical Methods for the Qualitative Assessment of Dynamic Models with Time Delay (R Package qualV)
title_full Statistical Methods for the Qualitative Assessment of Dynamic Models with Time Delay (R Package qualV)
title_fullStr Statistical Methods for the Qualitative Assessment of Dynamic Models with Time Delay (R Package qualV)
title_full_unstemmed Statistical Methods for the Qualitative Assessment of Dynamic Models with Time Delay (R Package qualV)
title_sort statistical methods for the qualitative assessment of dynamic models with time delay (r package qualv)
publisher Foundation for Open Access Statistics
series Journal of Statistical Software
issn 1548-7660
publishDate 2007-06-01
description Results of ecological models differ, to some extent, more from measured data than from empirical knowledge. Existing techniques for validation based on quantitative assessments sometimes cause an underestimation of the performance of models due to time shifts, accelerations and delays or systematic differences between measurement and simulation. However, for the application of such models it is often more important to reproduce essential patterns instead of seemingly exact numerical values. This paper presents techniques to identify patterns and numerical methods to measure the consistency of patterns between observations and model results. An orthogonal set of deviance measures for absolute, relative and ordinal scale was compiled to provide informations about the type of difference. Furthermore, two different approaches accounting for time shifts were presented. The first one transforms the time to take time delays and speed differences into account. The second one describes known qualitative criteria dividing time series into interval units in accordance to their main features. The methods differ in their basic concepts and in the form of the resulting criteria. Both approaches and the deviance measures discussed are implemented in an R package. All methods are demonstrated by means of water quality measurements and simulation data. The proposed quality criteria allow to recognize systematic differences and time shifts between time series and to conclude about the quantitative and qualitative similarity of patterns.
topic ecological modeling
qualitative validation criteria
time shift
R
url http://www.jstatsoft.org/v22/i08/paper
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