Abstract
In this paper, we study the problem of testing for parameter changes in generalized random coefficient autoregressive model (GRCA). The testing method is based on the monitoring scheme proposed by Na et al. (Stat. Methods Appl. 20:171-199, 2011), and the test statistic relies on the conditional least-squares estimator of an unknown parameter. Furthermore, under mild conditions, we obtain the asymptotic property of the test statistic. Some simulation studies are also conducted to investigate the finite sample performances of the proposed test.
Highlights
Consider the following one-order generalized random coefficient autoregressive model (GRCA( )): Yt = tYt– + εt, t =, ±, ±, . . . , ( . ) where (t, εt)τ is a random vector with E t εt = φt and Var t εtVφ,t σ ε,t σ ε,t σε,t
GRCA is designed for investigating the result of random perturbations of a dynamical system in engineering and economic data, and it has become one of the important models in the nonlinear time series context
GRCA has been studied by many authors
Summary
Introduction Consider the following one-order generalized random coefficient autoregressive model (GRCA( )): Yt = tYt– + εt, t = , ± , ± , . We consider the problem of testing for parameter changes in GRCA. Gombay and Serban [ ] proposed sequential tests to detect an abrupt change in any parameter, or in any collection of parameters of an autoregressive time series model.
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