Is Bootstrap Really Helpful in Point Process Statistics?
Martin Snethlage
Abstract
There are some papers which describe the use of bootstrap techniques in point process statistics. The aim of the present paper is to show that the form in which bootstrap is used there is dubious. In case of variance estimation of pair correlation function estimators the used bootstrap techniques lead to results which can be obtained simpler without simulation; furthermore, they differ from the desired results. The problem to obtain confidence regions for the intensity function of inhomogeneous Poisson processes can be easily solved without bootstrap techniques.
Create a lesson
Related papers
On diagonal sections of Markov products of copulas
Roman Drnovšek, Damjana Kokol Bukovšek, Nik Stopar
Beyond Discrepancy: Oracle Drift in Nonstationary Weighted Risk Minimization
Tobias Brock, Thomas Nagler
Estimating ratio of variance components in a balanced one-way random effect model
Somnath Mondal, Lakshmi Kanta Patra
Brown's loss function and estimation of the scale parameter and the entropy in scale mixture models with unknown location
Stavros Kourouklis
Finite-Sample Bounds for Fréchet Means of Dependent Data in Metric Spaces with Curvature Bounded Above
Zoraida F. Rico, Christof Schötz
On Eigenvector Statistics of Large-Dimensional Sample Covariance Matrices with Applications
Weiming Li, Zeng Li, Qinwen Wang