Regularized estimation for highly multivariate log Gaussian Cox processes

DOI10.1007/s11222-019-09911-yzbMath1437.62274arXiv1905.01455OpenAlexW2983367690WikidataQ126790599 ScholiaQ126790599MaRDI QIDQ2302515

Rasmus Waagepetersen, Achmad Choiruddin, Jean-François Coeurjolly, Francisco Cuevas-Pacheco

Publication date: 26 February 2020

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1905.01455

zbMATH Keywords

log Gaussian Cox processLassoelastic netmultivariate point processproximal Newton methodcross-pair correlation

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Estimation in multivariate analysis (62H12) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05) Applications of statistics to environmental and related topics (62P12) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

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Uses Software

• glmnet

Cites Work

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