Infill asymptotics for adaptive kernel estimators of spatial intensity

Marie-Colette van Lieshout*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)
49 Downloads (Pure)


We apply the Abramson principle to define adaptive kernel estimators for the intensity function of a spatial point process. We derive asymptotic expansions for the bias and variance under the regime that n independent copies of a simple point process in Euclidean space are superposed. The method is illustrated by means of a simple example and applied to tornado data.
Original languageEnglish
Article number12319
Pages (from-to)159–181
Number of pages23
JournalAustralian & New Zealand Journal of Statistics
Issue number1
Publication statusPublished - 1 Mar 2021


  • UT-Hybrid-D
  • bandwidth
  • infill asymptotics
  • intensity function
  • mean squared error
  • point process
  • adaptive kernel estimator


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