On Estimation of the Intensity Function of a Point Process

By M. V. Lieshout. Methodology and Computing in Applied Probability, 2011

47 citations recorded by the source corpus.

In this paper we review techniques for estimating the intensity function of a spatial point process. We present a unified framework of mass preserving general weight function estimators that encompasses both kernel and tessellation based estimators. We give explicit expressions for the first two moments of these estimators in terms of their product densities, and pay special attention to Poisson processes.

Subfields: Applied Mathematics, Economics and Econometrics, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/d64ce6dc4035b47a3916ec1f3cc27694c1c5b757

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Applied Mathematics

1. Ottmar Cronie
2. M. V. Lieshout

In Economics and Econometrics

1. Ottmar Cronie
2. M. V. Lieshout

In Environmental Engineering

1. Ottmar Cronie
2. M. V. Lieshout

Citations in the corpus

• A non-model-based approach to bandwidth selection for kernel estimators of spatial intensity functions (2018, background): “The relative merits of these approaches were investigated by Barr & Schoenberg (2010) and van Lieshout (2012).”