Shape analysis in the light of simplicial depth estimators
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F10%3A00063988" target="_blank" >RIV/00216224:14310/10:00063988 - isvavai.cz</a>
Result on the web
<a href="http://www1.maths.leeds.ac.uk/statistics/workshop/lasr2007/proceedings/" target="_blank" >http://www1.maths.leeds.ac.uk/statistics/workshop/lasr2007/proceedings/</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Shape analysis in the light of simplicial depth estimators
Original language description
In this paper we present the maximum simplicial depth estimator and compare it to the ordinary least square estimator in examples from 2D shape analysis focusing on bivariate and multivariate allometrical problems from zoology. We compare two types of estimators derived under different subsets of parametric space on the basis of the linear regression model. In applications where outliers in the x- or y-axis direction occur in the data and residuals from ordinary least-square (OLS) linear regression model are not normally distributed, we recommend the use of the maximum simplicial depth estimators.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
BB - Applied statistics, operational research
OECD FORD branch
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Result continuities
Project
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Continuities
R - Projekt Ramcoveho programu EK
Others
Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Systems Biology & Statistical Bioinformatics
ISBN
9780853162636
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
51-54
Publisher name
The University of Leeds
Place of publication
Leeds
Event location
LASR 2007 Leeds
Event date
Jan 1, 2007
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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