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Partial Functional Linear Models with ARCH Errors

Partial Functional Linear Models with ARCH Errors
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摘要 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. 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.
出处 《Open Journal of Statistics》 2018年第2期345-361,共17页 统计学期刊(英文)
关键词 ASYMPTOTIC NORMALITY ARCH(p) ERRORS FUNCTIONAL Principal Components Convergence Rate Least ABSOLUTE Deviation Asymptotic Normality ARCH(p) Errors Functional Principal Components Convergence Rate Least Absolute Deviation
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