Limit theory for unbiased and consistent estimators of statistics of random tessellations
Probability
2019-06-10 v1
Abstract
We observe a realization of a stationary generalized weighted Voronoi tessellation of the d-dimensional Euclidean space within a bounded observation window. Given a geometric characteristic of the typical cell, we use the minus-sampling technique to construct an unbiased estimator of the average value of this geometric characteristic. Under mild conditions on the weights of the cells, we establish variance asymptotics and the asymptotic normality of the unbiased estimator as the observation window tends to the whole space. Moreover, the weak consistency is shown for this estimator.
Keywords
Cite
@article{arxiv.1906.03097,
title = {Limit theory for unbiased and consistent estimators of statistics of random tessellations},
author = {Daniela Flimmel and Zbyněk Pawlas and Joseph E. Yukich},
journal= {arXiv preprint arXiv:1906.03097},
year = {2019}
}