| Autor: |
Myllymäki, Mari, Mrkvicka, Tomás, Grabarnik, Pavel, Seijo, Henri, Hahn, Ute |
| Rok vydání: |
2013 |
| Předmět: |
|
| Zdroj: |
Journal of the Royal Statistical Society: Series B (Statistical Methodology), 79 (2017): 381-404 |
| Druh dokumentu: |
Working Paper |
| DOI: |
10.1111/rssb.12172 |
| Popis: |
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 $\alpha$ 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 $\alpha$ and they yield $p$-values. We illustrate these tests using simulated and real point pattern data. |
| Databáze: |
arXiv |
| Externí odkaz: |
|
|
Nepřihlášeným uživatelům se plný text nezobrazuje |
K zobrazení výsledku je třeba se přihlásit.
|
