Article ID Journal Published Year Pages File Type
1149511 Journal of Statistical Planning and Inference 2010 8 Pages PDF
Abstract

We derive an asymptotic theory of nonparametric estimation for a time series regression model Zt=f(Xt)+Wt, where {Xt} and {Zt} are observed nonstationary processes, and {Wt} is an unobserved stationary process. The class of nonstationary processes allowed for {Xt} is a subclass of the class of null recurrent Markov chains. This subclass contains the random walk, unit root processes and nonlinear processes. The process {Wt} is assumed to be linear and stationary.

Related Topics
Physical Sciences and Engineering Mathematics Applied Mathematics
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