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Stochastic Reconstruction for Inhomogeneous 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%3A10434767" target="_blank" >RIV/00216208:11320/21:10434767 - isvavai.cz</a>

  • Result on the web

    <a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=HLDg4wqyEh" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=HLDg4wqyEh</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s11009-019-09738-0" target="_blank" >10.1007/s11009-019-09738-0</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Stochastic Reconstruction for Inhomogeneous Point Patterns

  • Original language description

    The stochastic reconstruction approach for point processes aims at producing independent patterns with the same properties as the observed pattern, without specifying any particular model. Instead a so-called energy functional is defined, based on a set of point process summary characteristics. It measures the dissimilarity between the observed pattern (input) and another pattern. The reconstructed pattern (output) is sought iteratively by minimising the energy functional. Hence, the output has approximately the same values of the prescribed summary characteristics as the input pattern. In this paper, we focus on inhomogeneous point patterns and apply formal hypotheses tests to check the quality of reconstructions in terms of the intensity function and morphological properties of the underlying point patterns. We argue that the current version of the algorithm available in the literature for inhomogeneous point processes does not produce outputs with appropriate intensity function. We propose modifications to the algorithm which can remedy this issue.

  • 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

    Methodology and Computing in Applied Probability

  • ISSN

    1387-5841

  • e-ISSN

  • Volume of the periodical

    23

  • Issue of the periodical within the volume

    2

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    21

  • Pages from-to

    527-547

  • UT code for WoS article

    000661508800006

  • EID of the result in the Scopus database

    2-s2.0-85070986887