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Global Envelope Tests for Spatial Processes

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Global Envelope Tests for Spatial Processes. / Myllymäki, Mari; Mrkvička, Tomáš; Grabarnik, Pavel; Seijo, Henri; Hahn, Ute.

I: Journal of the Royal Statistical Society, Series B (Statistical Methodology), Bind 79, Nr. 2, 20.03.2017, s. 381-404.

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avis › Tidsskriftartikel › Forskning › peer review

Harvard

Myllymäki, M, Mrkvička, T, Grabarnik, P, Seijo, H & Hahn, U 2017, 'Global Envelope Tests for Spatial Processes', Journal of the Royal Statistical Society, Series B (Statistical Methodology), bind 79, nr. 2, s. 381-404. https://doi.org/10.1111/rssb.12172

APA

Myllymäki, M., Mrkvička, T., Grabarnik, P., Seijo, H., & Hahn, U. (2017). Global Envelope Tests for Spatial Processes. Journal of the Royal Statistical Society, Series B (Statistical Methodology), 79(2), 381-404. https://doi.org/10.1111/rssb.12172

CBE

Myllymäki M, Mrkvička T, Grabarnik P, Seijo H, Hahn U. 2017. Global Envelope Tests for Spatial Processes. Journal of the Royal Statistical Society, Series B (Statistical Methodology). 79(2):381-404. https://doi.org/10.1111/rssb.12172

MLA

Myllymäki, Mari o.a.. "Global Envelope Tests for Spatial Processes". Journal of the Royal Statistical Society, Series B (Statistical Methodology). 2017, 79(2). 381-404. https://doi.org/10.1111/rssb.12172

Vancouver

Myllymäki M, Mrkvička T, Grabarnik P, Seijo H, Hahn U. Global Envelope Tests for Spatial Processes. Journal of the Royal Statistical Society, Series B (Statistical Methodology). 2017 mar 20;79(2):381-404. https://doi.org/10.1111/rssb.12172

Author

Myllymäki, Mari ; Mrkvička, Tomáš ; Grabarnik, Pavel ; Seijo, Henri ; Hahn, Ute. / Global Envelope Tests for Spatial Processes. I: Journal of the Royal Statistical Society, Series B (Statistical Methodology). 2017 ; Bind 79, Nr. 2. s. 381-404.

Bibtex

@article{2fa236717f4d482283a4edb2d154b462,
title = "Global Envelope Tests for Spatial Processes",
abstract = "Envelope tests are a popular tool in spatial statistics, where they are used in goodness-of-fit testing. These tests graphically compare an empirical function T(r) with its simulated counterparts from the null model. However, the type I error probability α is conventionally controlled for a fixed distance r only, whereas the functions are inspected on an interval of distances I. In this study, we propose two approaches related to Barnard{\textquoteright}s Monte Carlo test for building global envelope tests on I: (1) ordering the empirical and simulated functions based on their r-wise ranks among each other, and (2) the construction of envelopes for a deviation test. These new tests allow the a priori selection of the global α and they yield p-values. We illustrate these tests using simulated and real point pattern data.",
author = "Mari Myllym{\"a}ki and Tom{\'a}{\v s} Mrkvi{\v c}ka and Pavel Grabarnik and Henri Seijo and Ute Hahn",
year = "2017",
month = mar,
day = "20",
doi = "10.1111/rssb.12172",
language = "English",
volume = "79",
pages = "381--404",
journal = "Journal of the Royal Statistical Society, Series B (Statistical Methodology)",
issn = "1369-7412",
publisher = "John Wiley & Sons, Inc.",
number = "2",

}

RIS

TY - JOUR

T1 - Global Envelope Tests for Spatial Processes

AU - Myllymäki, Mari

AU - Mrkvička, Tomáš

AU - Grabarnik, Pavel

AU - Seijo, Henri

AU - Hahn, Ute

PY - 2017/3/20

Y1 - 2017/3/20

N2 - Envelope tests are a popular tool in spatial statistics, where they are used in goodness-of-fit testing. These tests graphically compare an empirical function T(r) with its simulated counterparts from the null model. However, the type I error probability α is conventionally controlled for a fixed distance r only, whereas the functions are inspected on an interval of distances I. In this study, we propose two approaches related to Barnard’s Monte Carlo test for building global envelope tests on I: (1) ordering the empirical and simulated functions based on their r-wise ranks among each other, and (2) the construction of envelopes for a deviation test. These new tests allow the a priori selection of the global α and they yield p-values. We illustrate these tests using simulated and real point pattern data.

AB - Envelope tests are a popular tool in spatial statistics, where they are used in goodness-of-fit testing. These tests graphically compare an empirical function T(r) with its simulated counterparts from the null model. However, the type I error probability α is conventionally controlled for a fixed distance r only, whereas the functions are inspected on an interval of distances I. In this study, we propose two approaches related to Barnard’s Monte Carlo test for building global envelope tests on I: (1) ordering the empirical and simulated functions based on their r-wise ranks among each other, and (2) the construction of envelopes for a deviation test. These new tests allow the a priori selection of the global α and they yield p-values. We illustrate these tests using simulated and real point pattern data.

U2 - 10.1111/rssb.12172

DO - 10.1111/rssb.12172

M3 - Journal article

VL - 79

SP - 381

EP - 404

JO - Journal of the Royal Statistical Society, Series B (Statistical Methodology)

JF - Journal of the Royal Statistical Society, Series B (Statistical Methodology)

SN - 1369-7412

IS - 2

ER -