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Activity Number:
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386
- Nonparametric Modeling II
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Type:
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Contributed
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Date/Time:
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Thursday, August 12, 2021 : 12:00 PM to 1:50 PM
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Sponsor:
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Section on Nonparametric Statistics
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Abstract #318073
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Title:
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Estimation and Inference in Generalized Spatial Partially Linear Varying Coefficient Models
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Author(s):
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Jingru Mu*
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Companies:
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Kansas State University, the Department of Statistics
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Keywords:
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penalized splines;
spatial data;
triangulation;
varying coefficient models;
bivariate splines
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Abstract:
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In this paper, we consider a class of generalized partially linear spatially varying coefficient models for data distributed over complex domains. We approximate the varying coefficient functions and linear coefficients via penalized bivariate splines over triangulation that can handle the complex boundary of the spatial domain. The asymptotic normality of estimated constant coefficients and the consistency of estimated varying coefficients are built up under some regularity conditions. We further propose a model selection approach to identify covariates with constant and varying effects. The performance of the proposed method is evaluated by simulation studies and the crash data in Texas.
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Authors who are presenting talks have a * after their name.
