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2019 Generalized threshold latent variable model
Yuanbo Li, Xunze Zheng, Chun Yip Yau
Electron. J. Statist. 13(1): 2043-2092 (2019). DOI: 10.1214/19-EJS1571


This article proposes a generalized threshold latent variable model for flexible threshold modeling of time series. The proposed model encompasses several existing models, and allows a discrete valued threshold variable. Sufficient conditions for stationarity and ergodicity are investigated. The minimum description length principle is applied to formulate a criterion function for parameter estimation and model selection. A computationally efficient procedure for optimizing the criterion function is developed based on a genetic algorithm. Consistency and weak convergence of the parameter estimates are established. Moreover, simulation studies and an application for initial public offering data are presented to illustrate the proposed methodology.


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Yuanbo Li. Xunze Zheng. Chun Yip Yau. "Generalized threshold latent variable model." Electron. J. Statist. 13 (1) 2043 - 2092, 2019.


Received: 1 April 2018; Published: 2019
First available in Project Euclid: 22 June 2019

zbMATH: 07080068
MathSciNet: MR3973132
Digital Object Identifier: 10.1214/19-EJS1571

Primary: 62M10

Keywords: compound Poisson process , ergodicity , Genetic algorithm , minimum description length principle , multiple-threshold , piecewise modeling


Vol.13 • No. 1 • 2019
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