Nonlinear least squares estimation of the periodic EXPAR(1) model

S. Becila and M. Merzougui

Communications in Statistics - Theory and Methods, 2022, vol. 51, issue 15, 5369-5381

Abstract: In this paper, we study the strong consistency and asymptotic normality properties of nonlinear least squares (NLS) estimator of the periodic EXPAR(1) model. The general statistical literature on estimation of nonlinear models of Gallant and White is used. Simulation study and one real example are given to assess the performance of this NLS.

Date: 2022
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DOI: 10.1080/03610926.2020.1839099

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