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ASYMPTOTIC NORMALITY OF WAVELET ESTIMATOR IN HETEROSCEDASTIC MODEL WITH α-MIXING ERRORS 被引量:3

ASYMPTOTIC NORMALITY OF WAVELET ESTIMATOR IN HETEROSCEDASTIC MODEL WITH α-MIXING ERRORS
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摘要 Consider heteroscedastic regression model Yni= g(xni) + σniεni (1 〈 i 〈 n), where σ2ni= f(uni), the design points (xni, uni) are known and nonrandom, g(.) and f(.) are unknown functions defined on closed interval [0, 1], and the random errors (εni, 1 ≤i≤ n) axe assumed to have the same distribution as (ξi, 1 ≤ i ≤ n), which is a stationary and a-mixing time series with Eξi =0. Under appropriate conditions, we study asymptotic normality of wavelet estimators of g(.) and f(.). Finite sample behavior of the estimators is investigated via simulations, too.
作者 Hanying LIANG
出处 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2011年第4期725-737,共13页 系统科学与复杂性学报(英文版)
基金 supported by the National Natural Science Foundation of China under Grant No.10871146 the Grant MTM2008-03129 from the Spanish Ministry of Science and Innovation
关键词 Α-MIXING asymptotic normality heteroscedastic regression model wavelet estimator. 渐近正态性 小波估计 混合时间 异方差模型 异方差回归模型 随机误差 UNI 未知函数
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