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Monte Carlo testing in spatial statistics, with applications to spatial residuals

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

  • Tomáš Mrkvička, University of South Bohemia, Tjekkiet
  • Samuel Soubeyrand, BioSP, INRA, Frankrig
  • Mari Myllymäki, Natural Resources Institute Finland (Luke), Finland
  • Pavel Grabarnik, Russian Academy of Sciences, Rusland
  • Ute Hahn
This paper reviews recent advances made in testing in spatial statistics and discussed at the Spatial Statistics conference in Avignon 2015. The rank and directional quantile envelope tests are discussed and practical rules for their use are provided. These tests are global envelope tests with an appropriate type I error probability. Two novel examples are given on their usage. First, in addition to the test based on a classical one-dimensional summary function, the goodness-of-fit of a point process model is evaluated by means of the test based on a higher dimensional functional statistic, namely a two-dimensional smoothed residual field. Second, a goodness-of-fit test of a geostatistical model is performed based on two-dimensional raw residuals.
OriginalsprogEngelsk
TidsskriftSpatial Statistics
Vol/bind18
NummerA
Sider (fra-til)40-53
ISSN2211-6753
DOI
StatusUdgivet - nov. 2016

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