Adaptive lasso and Dantzig selector for spatial point processes intensity estimation

Achmad Choiruddin, Jean François Coeurjolly, Frédérique Letué

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Lasso and Dantzig selector are standard procedures able to perform variable selection and estimation simultaneously. This paper is concerned with extending these procedures to spatial point process intensity estimation. We propose adaptive versions of these procedures, develop efficient computational methodologies and derive asymptotic results for a large class of spatial point processes under an original setting where the number of parameters, i.e. the number of spatial covariates considered, increases with the expected number of data points. Both procedures are compared theoretically, in a simulation study, and in a real data example.

Original languageEnglish
Pages (from-to)1849-1876
Number of pages28
JournalBernoulli
Volume29
Issue number3
DOIs
Publication statusPublished - Aug 2023

Keywords

  • Estimating equations
  • high-dimensional statistics
  • linear programming
  • regularization methods
  • spatial point pattern

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