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

• URL: http://arxiv.org/abs/2505.14529v1
• Date: Tue, 20 May 2025 15:48:45 GMT
• Title: A simple estimator of the correlation kernel matrix of a determinantal point process
• Authors: Christian Gouriéroux, Yang Lu,
• Abstract summary: This paper proposes a closed form estimator of the Determinantal Point Process (DPP)<n>We prove the consistency and normality of our estimator, as well as its large deviation properties.
• Score: 3.692410936160711
• License: http://creativecommons.org/licenses/by/4.0/
• 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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