Some Robust Estimation Tools for Multivariate Models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F15%3A00449741" target="_blank" >RIV/67985807:_____/15:00449741 - isvavai.cz</a>
Result on the web
<a href="http://msed.vse.cz/msed_2015/article/7-Kalina-Jan-paper.pdf" target="_blank" >http://msed.vse.cz/msed_2015/article/7-Kalina-Jan-paper.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Some Robust Estimation Tools for Multivariate Models
Original language description
Standard procedures of multivariate statistics and data mining for the analysis of multivariate data are known to be vulnerable to the presence of outlying and/or highly influential observations. This paper has the aim to propose and investigate specificapproaches for two situations. First, we consider clustering of categorical data. While attention has been paid to sensitivity of standard statistical and data mining methods for categorical data only recently, we aim at modifying standard distance measures between clusters of such data. This allows us to propose a hierarchical agglomerative cluster analysis for two-way contingency tables with a large number of categories, based on a regularized measure of distance between two contingency tables. Suchproposal improves the robustness to the presence of measurement errors for categorical data. As a second problem, we investigate the nonlinear version of the least weighted squares regression for data with a continuous response. Our aim i
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
<a href="/en/project/GA13-17187S" target="_blank" >GA13-17187S: Constructing Advanced Comprehensible Classifiers</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
The 9th International Days of Statistics and Economics Conference Proceedings
ISBN
978-80-87990-06-3
ISSN
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e-ISSN
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Number of pages
10
Pages from-to
713-722
Publisher name
VŠE
Place of publication
Praha
Event location
Prague
Event date
Sep 10, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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