Some properties of local weighted second-order statistics for spatio-temporal point processes

Marianna Siino, Giada Adelfio, Francisco J. Rodríguez-Cortés, Jorge Mateu

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Diagnostics of goodness-of-fit in the theory of point processes are often considered through the transformation of data into residuals as a result of a thinning or a rescaling procedure. We alternatively consider here second-order statistics coming from weighted measures. Motivated by Adelfio and Schoenberg (2009) for the temporal and spatial cases, we consider an extension to the spatio-temporal context in addition to focussing on local characteristics. In particular, our proposed method assesses goodness-of-fit of spatio-temporal models by using local weighted secondorder statistics, computed after weighting the contribution of each observed point by the inverse of the conditional intensity function that identifies the process. Weighted second-order statistics directly apply to data without assuming homogeneity nor transforming the data into residuals, eliminating thus the sampling variability due to the use of a transforming procedure. We provide some characterisations and show a number of simulation studies.
Original languageEnglish
Pages (from-to)149-168
Number of pages20
JournalStochastic Environmental Research and Risk Assessment
Volume34
Publication statusPublished - 2019

All Science Journal Classification (ASJC) codes

  • Environmental Engineering
  • Environmental Chemistry
  • Safety, Risk, Reliability and Quality
  • Water Science and Technology
  • General Environmental Science

Fingerprint

Dive into the research topics of 'Some properties of local weighted second-order statistics for spatio-temporal point processes'. Together they form a unique fingerprint.

Cite this