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Testing the first-order separability hypothesis for spatio-temporal point patterns

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10434529" target="_blank" >RIV/00216208:11320/21:10434529 - isvavai.cz</a>

  • Result on the web

    <a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=Od5X6G6MFm" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=Od5X6G6MFm</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.csda.2021.107245" target="_blank" >10.1016/j.csda.2021.107245</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Testing the first-order separability hypothesis for spatio-temporal point patterns

  • Original language description

    First-order separability of a spatio-temporal point process plays a fundamental role in the analysis of spatio-temporal point pattern data. While it is often a convenient assumption that simplifies the analysis greatly, existing non-separable structures should be accounted for in the model construction. Three different tests are proposed to investigate this hypothesis as a step of preliminary data analysis. The first two tests are exact or asymptotically exact for Poisson processes. The first test based on permutations and global envelopes allows one to detect at which spatial and temporal locations or lags the data deviate from the null hypothesis. The second test is a simple and computationally cheap chi(2)-test. The third test is based on stochastic reconstruction method and can be generally applied for non-Poisson processes. The performance of the first two tests is studied in a simulation study for Poisson and non-Poisson models. The third test is applied to the real data of the UK 2001 epidemic foot and mouth disease. (C) 2021 The Author(s). Published by Elsevier B.V.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10103 - Statistics and probability

Result continuities

  • 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)

Others

  • Publication year

    2021

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Computational Statistics and Data Analysis

  • ISSN

    0167-9473

  • e-ISSN

  • Volume of the periodical

    161

  • Issue of the periodical within the volume

    September

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    20

  • Pages from-to

    107245

  • UT code for WoS article

    000656871500014

  • EID of the result in the Scopus database

    2-s2.0-85103965352