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Abstract This paper investigates the quasi-maximum likelihood estimator (QMLE) of the structure-changed and two-regime threshold double autoregressive model. It is shown that both the estimated threshold and change-point are n… Click to show full abstract
Abstract This paper investigates the quasi-maximum likelihood estimator (QMLE) of the structure-changed and two-regime threshold double autoregressive model. It is shown that both the estimated threshold and change-point are n -consistent, and they converge weakly to the smallest minimizer of a compound Poisson process and the location of minima of a two-sided random walk, respectively. Other estimated parameters are n − consistent and asymptotically normal. The performance of the QMLE is assessed via simulation studies and a real example is given to illustrate our procedure.
Journal Title: Journal of Statistical Planning and Inference
Year Published: 2020
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