A simple estimator of the correlation kernel matrix of a determinantal point process

Christian Gouriéroux, Yang Lu
5/20/2025
stat.MLcs.LG

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Abstract

The Determinantal Point Process (DPP) is a parameterized model for multivariate binary variables, characterized by a correlation kernel matrix. This paper proposes a closed form estimator of this kernel, which is particularly easy to implement and can also be used as a starting value of learning algorithms for maximum likelihood estimation. We prove the consistency and asymptotic normality of our estimator, as well as its large deviation properties.

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Cite this paper

@article{gouriroux2025simple,
  title  = {A simple estimator of the correlation kernel matrix of a determinantal point process},
  author = {Christian Gouriéroux and Yang Lu},
  year   = {2025},
  eprint = {2505.14529},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2505.14529v1}
}

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