On local linear regression for strongly mixing random fields

Mohamed El Machkouri, Khalifa Es-Sebaiy and Idir Ouassou

Journal of Multivariate Analysis, 2017, vol. 156, issue C, 103-115

Abstract: We investigate the local linear kernel estimator of the regression function g of a stationary and strongly mixing real random field observed over a general subset of the lattice Zd. Assuming that g is differentiable with derivative g′, we provide a new criterion on the mixing coefficients for the consistency and the asymptotic normality of the estimators of g and g′ under mild conditions on the bandwidth parameter. Our results improve the work of Hallin et al. (2004) in several directions.

Keywords: Local linear regression estimation; Strong mixing; Random fields; Asymptotic normality (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.jmva.2017.02.002

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