Goodness-of-fit tests for complete spatial randomness based on Minkowski functionals of binary images

Journal article


Publication Details

Author(s): Ebner B, Henze N, Klatt MA, Mecke K
Journal: Electronic Journal of Statistics
Publication year: 2018
Volume: 12
Journal issue: 2
Pages range: 2873-2904
ISSN: 1935-7524


Abstract

We propose a class of goodness-of-fit tests for complete spatial randomness (CSR). In contrast to standard tests, our procedure utilizes a transformation of the data to a binary image, which is then characterized by geometric functionals. Under a suitable limiting regime, we derive the asymptotic distribution of the test statistics under the null hypothesis and almost sure limits under certain alternatives. The new tests are computationally efficient, and simulations show that they are strong competitors to other tests of CSR. The tests are applied to a real data set in gamma-ray astronomy, and immediate extensions are presented to encourage further work.


FAU Authors / FAU Editors

Mecke, Klaus Prof. Dr.
Lehrstuhl für Theoretische Physik


External institutions with authors

Karlsruhe Institute of Technology (KIT)


How to cite

APA:
Ebner, B., Henze, N., Klatt, M.A., & Mecke, K. (2018). Goodness-of-fit tests for complete spatial randomness based on Minkowski functionals of binary images. Electronic Journal of Statistics, 12(2), 2873-2904. https://dx.doi.org/10.1214/18-EJS1467

MLA:
Ebner, Bruno, et al. "Goodness-of-fit tests for complete spatial randomness based on Minkowski functionals of binary images." Electronic Journal of Statistics 12.2 (2018): 2873-2904.

BibTeX: 

Last updated on 2019-22-03 at 13:08