Research ArticleOpen AccessGoogle Scholar indexed
Partial Functional Linear Models with ARCH Errors
College of Applied Sciences, Beijing University of Technology, Beijing, China
College of Applied Sciences, Beijing University of Technology, Beijing, China
College of Applied Sciences, Beijing University of Technology, Beijing, China
- 1 College of Applied Sciences, Beijing University of Technology, Beijing, China
- 2 College of Applied Sciences, Beijing University of Technology, Beijing, China
- 3 College of Applied Sciences, Beijing University of Technology, Beijing, China
Open Journal of Statistics·Volume 08 (2018)·Pages 345–361·Published 30 March 2018·DOI10.4236/ojs.2018.82023
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Abstract
In this paper, the estimation of the parameters in partial functional linear models with ARCH(p) errors is discussed. With employing the functional principle component, a hybrid estimating method is suggested. The asymptotic normality of the proposed estimators for both the linear parameter in the mean model and the parameter in the ARCH error model is obtained, and the convergence rate of the slope function estimate is established. Besides, some simulations and a real data analysis are conducted for illustration, and it is shown that the proposed method performs well with a finite sample.
KeywordsAsymptotic NormalityARCH(p) ErrorsFunctional Principal ComponentsConvergence RateLeast Absolute Deviation
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