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Statistical Inference on the Parametric Component in Partially Linear Spatial Autoregressive Models
Authors:Tizheng Li  Changlin Mei
Affiliation:1. Department of Mathematics, School of Science, Xi’an University of Architecture and Technology, Xi’an, People’s Republic of China;2. Department of Statistics, School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, People’s Republic of China
Abstract:A statistical test procedure is proposed to check whether the parameters in the parametric component of the partially linear spatial autoregressive models satisfy certain linear constraint conditions, in which a residual-based bootstrap procedure is suggested to derive the p-value of the test. Some simulations are conducted to assess the performance of the test and the results show that the bootstrap approximation to the null distribution of the test statistic is valid and the test is of satisfactory power. Furthermore, a real-world example is given to demonstrate the application of the proposed test.
Keywords:Bootstrap  Local polynomial fitting  Partially linear spatial autoregressive model  Profile quasi-maximum likelihood estimation  Spatial dependence
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