An Adaptive Empirical Likelihood Test For Time Series Models
نویسندگان
چکیده
where both m(·) and σ(·) are unknown functions defined over R, the data {(Xt, Yt)}t=1 are weakly dependent stationary time series, and et is an error process with zero mean and unit variance. Suppose that {mθ(·)|θ ∈ Θ} is a family of parametric specification to the regression function m(x) where θ ∈ R is an unknown parameter belonging to a parameter space Θ. This paper considers testing the validity of the parametric specification of mθ(x) against a series of local alternatives, that is to test
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