Divergence-based tests of homogeneity for spatial data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F14%3A00210346" target="_blank" >RIV/68407700:21340/14:00210346 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/s00362-013-0554-6" target="_blank" >http://dx.doi.org/10.1007/s00362-013-0554-6</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s00362-013-0554-6" target="_blank" >10.1007/s00362-013-0554-6</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Divergence-based tests of homogeneity for spatial data

Popis výsledku v původním jazyce

The problem of testing homogeneity in contingency tables when the data are spatially correlated is considered.We derive statistics defined as divergences between unrestricted and restricted estimated joint cell probabilities and we show that they are asymptotically distributed as linear combinations of chi-square random variables under the null hypothesis of homogeneity. Monte Carlo simulation experiments are carried out to investigate the behavior of the new divergence test statistics and to make comparisons with the statistics that do not take into account the spatial correlation.We show that some of the introduced divergence test statistics have a significantly better behavior than the classical chi-square test for the problem under consideration when we compare them on the basis of the simulated sizes and powers.

Název v anglickém jazyce

Divergence-based tests of homogeneity for spatial data

Popis výsledku anglicky

The problem of testing homogeneity in contingency tables when the data are spatially correlated is considered.We derive statistics defined as divergences between unrestricted and restricted estimated joint cell probabilities and we show that they are asymptotically distributed as linear combinations of chi-square random variables under the null hypothesis of homogeneity. Monte Carlo simulation experiments are carried out to investigate the behavior of the new divergence test statistics and to make comparisons with the statistics that do not take into account the spatial correlation.We show that some of the introduced divergence test statistics have a significantly better behavior than the classical chi-square test for the problem under consideration when we compare them on the basis of the simulated sizes and powers.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název periodika

Statistical Papers

ISSN

0932-5026

e-ISSN

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Svazek periodika

55

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

19

Strana od-do

1059-1077

Kód UT WoS článku

000343046200010

EID výsledku v databázi Scopus

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