SLICED INVERSE REGRESSION AND INDEPENDENCE IN RANDOM MARKED SETS WITH COVARIATES
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F13%3A10159392" target="_blank" >RIV/00216208:11320/13:10159392 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
SLICED INVERSE REGRESSION AND INDEPENDENCE IN RANDOM MARKED SETS WITH COVARIATES
Original language description
Dimension reduction of multivariate data was developed by Y. Guan for point processes with Gaussian random fields as covariates. The generalization to fibre and surface processes is straightforward. In inverse regression methods, we suggest slicing basedon geometrical marks. An investigation of the properties of this method is presented in simulation studies of random marked sets. In a refined model for dimension reduction, the second-order central subspace is analyzed in detail. A real data pattern istested for independence of a covariate.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
BA - General mathematics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GAP201%2F10%2F0472" target="_blank" >GAP201/10/0472: Stochastic geometry - inhomogeneity, marking, dynamics and stereology</a><br>
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Advances in Applied Probability
ISSN
0001-8678
e-ISSN
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Volume of the periodical
45
Issue of the periodical within the volume
3
Country of publishing house
GB - UNITED KINGDOM
Number of pages
19
Pages from-to
626-644
UT code for WoS article
000325444200002
EID of the result in the Scopus database
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