Abstract
This paper considers the local linear estimation of a multivariate regression function and its derivatives for a stationary long memory (long range dependent) nonparametric spatio-temporal regression model. Under some mild regularity assumptions, the pointwise strong convergence, the uniform weak consistency with convergence rates and the joint asymptotic distribution of the estimators are established. A simulation study is carried out to illustrate the performance of the proposed estimators.
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Wang, L. The nonparametric estimation of long memory spatio-temporal random field models. Sci. China Math. 58, 1115–1128 (2015). https://doi.org/10.1007/s11425-014-4833-z
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DOI: https://doi.org/10.1007/s11425-014-4833-z
Keywords
- asymptotic behaviors
- local linear regression estimation
- long memory random fields
- spatio-temporal random field models