SUPERVISED NONPARAMETRIC CLASSIFICATION IN THE CONTEXT OF REPLICATED POINT PATTERNS

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3A10447848" target="_blank" >RIV/00216208:11320/22:10447848 - isvavai.cz</a>

Result on the web

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=AQ0SX49DqO" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=AQ0SX49DqO</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5566/ias.2652" target="_blank" >10.5566/ias.2652</a>

Result language

angličtina

Original language name

SUPERVISED NONPARAMETRIC CLASSIFICATION IN THE CONTEXT OF REPLICATED POINT PATTERNS

Original language description

A spatial point pattern is a collection of points in space, representing, e.g. observed locations of trees, bird nests, centers of cells in a histological sample, etc. When several independent realizations of the underlying stochastic process are observed, these realizations are referred to as replicated point patterns. The main objective of this paper is to classify a newly observed pattern into one of the existing classes using a supervised nonparametric classification method, namely the Bayes classifier in combination with the k-nearest neighbors algorithms and the kernel regression method. The dissimilarity between a pair of patterns is defined using the functional summaries extracted from the point patterns via the Cramer-von Mises or Kolmogorov-Smirnov type formula. A set of simulation experiments is presented to investigate the performance of the proposed classifier with a dissimilarity measure based on functional summaries, such as the pair correlation function. The application of such a classifier to a real point pattern dataset is also illustrated.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10103 - Statistics and probability

Project

<a href="/en/project/GA19-04412S" target="_blank" >GA19-04412S: New approaches to modeling and statistics of random sets</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Image Analysis and Stereology

ISSN

1580-3139

e-ISSN

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Volume of the periodical

41

Issue of the periodical within the volume

2

Country of publishing house

SI - SLOVENIA

Number of pages

18

Pages from-to

57-74

UT code for WoS article

000824607400001

EID of the result in the Scopus database

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