Multivariate regression estimation local polynomial fitting for time series

Elias Masry

Stochastic Processes and their Applications, 1996, vol. 65, issue 1, 81-101

Abstract: We consider the estimation of the multivariate regression function m(x1, ..., xd) = E[[psi](Yd)X1 = x1, ..., Xd = xd], and its partial derivatives, for stationary random processes Yi, Xi using local higher-order polynomial fitting. Particular cases of [psi] yield estimation of the conditional mean, conditional moments and conditional distributions. Joint asymptotic normality is established for estimates of the regression function and its partial derivatives for strongly mixing and [varrho]-mixing processes. Expressions for the bias and variance/covariance matrix (of the asymptotically normal distribution) for these estimators are given.

Keywords: Multivariate; regression; estimation; Local; polynomial; fitting; Mixing; processes; Joint; asymptotic; normality (search for similar items in EconPapers)
Date: 1996
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Citations: View citations in EconPapers (66)

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