Uniform Convergence Rates of Kernel Estimators with Heterogenous, Dependent Data

Dennis Kristensen

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

Abstract: The main uniform convergence results of Hansen (2008) are generalized in two directions: Data is allowed to (i) be heterogenously dependent and (ii) depend on a (possibly unbounded) parameter. These results are useful in semiparametric estimation problems involving time-inhomogenous models and/or sampling of continuous-time processes. The usefulness of these results are demonstrated by two applications: Kernel regression estimation of a time-varying AR(1) model , and the kernel density estimation of a Markov chain that has not been intialized at its stationary distribution.

Keywords: Nonparametric estimation; uniform consistency; kernel estimation; density estimation; heterogeneous time series (search for similar items in EconPapers)
JEL-codes: C14 C32 (search for similar items in EconPapers)
Pages: 13
Date: 2008-07-01
New Economics Papers: this item is included in nep-ets and nep-ore
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Citations: View citations in EconPapers (2)

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Related works:
Journal Article: UNIFORM CONVERGENCE RATES OF KERNEL ESTIMATORS WITH HETEROGENEOUS DEPENDENT DATA (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:aah:create:2008-37

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