Empirical Likelihood Inference for Partial Functional Linear Regression Models Based on B-spline


  •  Mingao Yuan    
  •  Yue Zhang    

Abstract

In this paper, we apply empirical likelihood method to infer for the regression parameters in the partial functional linear regression models based on B-spline. We prove that the empirical log-likelihood ratio for the regression parameters converges in law to a weighted sum of independent chi-square distributions. Our simulation shows that the proposed empirical likelihood method produces more accurate confidence regions in terms of coverage probability than the asymptotic normality method.



This work is licensed under a Creative Commons Attribution 4.0 License.
  • Issn(Print): 1927-7032
  • Issn(Onlne): 1927-7040
  • Started: 2012
  • Frequency: bimonthly

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