Isotropy of a point process, defined as invariance of the distribution under rotation, is often assumed in spatial statistics. Formal tests for the hypothesis of isotropy can be created by comparing directional summary statistics in different directions. In this paper, the statistical powers of tests based on a variety of summary statistics and several choices of deviance measures are compared in a simulation study. Four models for anisotropic point processes are considered covering both regular and clustered cases. We discuss the robustness of the results to changes of the tuning parameters, and highlight the strengths and limitations of the methods
The deviation test belong to core tools in point process statistics, where hypotheses are typically ...
The analysis of directional data is an area of statistics concerned with observations collected init...
Statistical analysis of point processes often assumes that the underlying process is isotropic in t...
Isotropy of a point process, defined as invariance of the distribution\ua0under rotation, is often a...
We develop a new methodology for estimating and testing the form of anisotropy of homogeneous spatia...
The assumption of direction invariance, i.e., isotropy, is often made in the practical analysis of s...
A common requirement for spatial analysis is the modeling of the second-order structure. While the a...
A spatial point pattern is called anisotropic if its spatial structure depends on direction. Several...
Stationarity in space presents two aspects: homogeneity and isotropy. They correspond respectively ...
This paper develops a new methodology for estimating and testing the form of anisotropy of homogeneo...
The assumption of direction invariance, i.e. isotropy, is often made in the practical analysis of sp...
Paper deals with a problem of testing isotropy against geometric anisotropy for Gaussian spatial dat...
Second-order spatio-temporal orientation methods provide a natural tool for the analysis of anisotro...
A two-dimensional point process, if considered as a random measure, can be expressed as a countable ...
Analyses of spatial point patterns tend to focus on deviations from randomness by either clustering ...
The deviation test belong to core tools in point process statistics, where hypotheses are typically ...
The analysis of directional data is an area of statistics concerned with observations collected init...
Statistical analysis of point processes often assumes that the underlying process is isotropic in t...
Isotropy of a point process, defined as invariance of the distribution\ua0under rotation, is often a...
We develop a new methodology for estimating and testing the form of anisotropy of homogeneous spatia...
The assumption of direction invariance, i.e., isotropy, is often made in the practical analysis of s...
A common requirement for spatial analysis is the modeling of the second-order structure. While the a...
A spatial point pattern is called anisotropic if its spatial structure depends on direction. Several...
Stationarity in space presents two aspects: homogeneity and isotropy. They correspond respectively ...
This paper develops a new methodology for estimating and testing the form of anisotropy of homogeneo...
The assumption of direction invariance, i.e. isotropy, is often made in the practical analysis of sp...
Paper deals with a problem of testing isotropy against geometric anisotropy for Gaussian spatial dat...
Second-order spatio-temporal orientation methods provide a natural tool for the analysis of anisotro...
A two-dimensional point process, if considered as a random measure, can be expressed as a countable ...
Analyses of spatial point patterns tend to focus on deviations from randomness by either clustering ...
The deviation test belong to core tools in point process statistics, where hypotheses are typically ...
The analysis of directional data is an area of statistics concerned with observations collected init...
Statistical analysis of point processes often assumes that the underlying process is isotropic in t...