Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1156180 | Stochastic Processes and their Applications | 2009 | 16 Pages |
Abstract
We study the asymptotic behaviour of the empirical distribution function derived from a stationary marked point process when a convex sampling window is expanding without bounds in all directions. We consider a random field model which assumes that the marks and the points are independent and admits dependencies between the marks. The main result is the weak convergence of the empirical process under strong mixing conditions on both independent components of the model. Applying an approximation principle weak convergence can be also shown for appropriately weighted empirical process defined from a stationary d-dimensional germ-grain process with dependent grains.
Related Topics
Physical Sciences and Engineering
Mathematics
Mathematics (General)
Authors
Zbyněk Pawlas,