Asymptotic approximation of the likelihood of stationary determinantal point processes

DOI10.1111/sjos.12613arXiv2103.02310OpenAlexW3134560421WikidataQ114078095 ScholiaQ114078095MaRDI QIDQ6073427

Arnaud Poinas, Frédéric Lavancier

Publication date: 11 October 2023

Published in: Scandinavian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2103.02310

zbMATH Keywords

determinantal point processmaximum likelihood inferencerepulsive

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

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• Quantifying repulsiveness of determinantal point processes
• An introduction to the theory of point processes
• Random point fields associated with certain Fredholm determinants. I: Fermion, Poisson and Boson point processes.
• The Schur complement and its applications
• Monte Carlo with determinantal point processes
• On the zeros of the spectrogram of white noise
• Determinantal random point fields
• Determinantal Point Processes for Machine Learning
• Contrast Estimation for Parametric Stationary Determinantal Point Processes
• A Cellular Network Model with Ginibre Configured Base Stations
• The coincidence approach to stochastic point processes
• Assessing the accuracy of the maximum likelihood estimator: Observed versus expected Fisher information
• Adaptive estimating function inference for nonstationary determinantal point processes
• Determinantal Point Process Models and Statistical Inference
• Concentration of Lipschitz Functionals of Determinantal and Other Strong Rayleigh Measures
• Determinantal Point Processes for Image Processing