An Efficient Approach for Estimating Parameters and Nonparametric Functions in Spatio-temporal Semi-parametric Regression Models
In this work, the regression problem of spatiotemporal data is studied under the framework of the semiparametric model. A new kernel estimator for the spatiotemporally correlated data is proposed to estimate nonparametric functions, and we show the new method can improve the estimation efficiency of nonparametric functions from existing kernel methods such as the local linear regression.
Figure 1: The trajectory of the standard deviation of the function g(t) over the sampling time points. (1) WCX (Wang et al. 2005, JASA). (2) LLR (Liu et al., 2021, JMVA). (3) The proposed PWLLR-7. (4) The proposed PWLLR-40.