A0401
Title: Moment convergence of the generalized maximum composite likelihood estimators for determinantal point processes
Authors: Kou Fujimori - Shinshu University (Japan) [presenting]
Yasutaka Shimizu - Waseda University (Japan)
Sota Sakamoto - Waseda University (Japan)
Abstract: The maximum composite likelihood estimator for parametric models of determinantal point processes (DPPs) is discussed. Since the joint intensities of these point processes are given by determinant of positive definite kernels, we have the explicit form of the joint intensities for every order. This fact enables us to consider the generalized maximum composite likelihood estimator for any order. We introduce the two-step generalized composite likelihood estimator and show the moment convergence of the estimator under stationarity. Moreover, our results can yield information criteria for statistical model selection within DPPs.
