A Thinned Block Bootstrap Variance Estimation Procedure for Inhomogeneous Spatial Point Patterns

By Yongtao Guan, Ji Meng Loh. 2007

58 citations recorded by the source corpus.

Subfields: Applied Mathematics, Environmental Engineering, Geometry and Topology

View Paper: https://www.semanticscholar.org/paper/cb3538cfcd8577f8ef63a7fce2626c341eb89b24

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. Yongtao Guan
2. Rasmus Waagepetersen
3. Jesper Møller
4. Adrian Baddeley
5. M. V. Lieshout
6. B. Vo
7. Rolf Turner

In Environmental Engineering

1. Yongtao Guan
2. Rasmus Waagepetersen
3. Jesper Møller

In Geometry and Topology

1. Yongtao Guan
2. Rasmus Waagepetersen
3. Jesper Møller

Citations in the corpus

• On Consistent Nonparametric Intensity Estimation for Inhomogeneous Spatial Point Processes (2008, methodology): “It holds for commonly used spatial point process models including, but not limited to a large class of log-Gaussian Cox process models and inhomogeneous Neyman–Scott process models (e.g., Heinrich 1985; Guan and Loh 2007).”
• Estimating functions for inhomogeneous spatial point processes with incomplete covariate data (2008, background): “However, for non-Poisson processes with intensity function λ(·;β), (1) may still be useful for estimating β, see Schoenberg (2005), Waagepetersen (2007), Møller & Waagepetersen (2006), and Guan & Loh (2007).”
• Two‐step estimation for inhomogeneous spatial point processes (2009, background): “We moreover provide less restrictive conditions for the asymptotic normality of β̂ than those in Waagepetersen (2007) and Guan and Loh (2007).”