Estimation in functional partially linear spatial autoregressive model

Authors : Yuping Hu, Siyu Wu, Sanying Feng

Pages : 1196-1217

Doi:10.15672/hujms.1324888

View : 141 | Download : 136

Publication Date : 2024-08-27

Article Type : Research Paper

Abstract :Functional regression has been a hot topic in statistical research. However, not much work has been done when response variables are cross-sectionally dependent variables and explanatory variables contain a real-valued scalar variable and a functional-valued random variable. In this paper, we consider a new functional partially linear spatial autoregressive model. Based on the functional principal components analysis and basis function approximation, we obtain the estimators of the unknown parameter and functions through the instrumental variables estimation method. The asymptotic normality and convergence rates of estimators are proved under some mild conditions. In addition, we illustrate the finite sample performance of the proposed estimation method through simulation study and a real data analysis.
Keywords : Functional partial linear spatial autoregressive model, spatial autoregression, functional principal component analysis, instrument variable