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Nonparametric M-estimation for Functional Stationary Ergodic Data

Nonparametric M-estimation for Functional Stationary Ergodic Data
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摘要 This paper considers a nonparametric M-estimator of a regression function for functional stationary ergodic data.More precisely,in the ergodic data setting,we consider the regression of a real random variable Y over an explanatory random variable X taking values in some semi-metric abstract space.Under some mild conditions,the weak consistency and the asymptotic normality of the M-estimator are established.Furthermore,a simulated example is provided to examine the finite sample performance of the M-estimator. This paper considers a nonparametric M-estimator of a regression function for functional stationary ergodic data. More precisely, in the ergodic data setting, we consider the regression of a real random variable Y over an explanatory random variable X taking values in some semi-metric abstract space. Under some mild conditions, the weak consistency and the asymptotic normality of the M-estimator are established. Furthermore,a simulated example is provided to examine the finite sample performance of the M-estimator.
出处 《Acta Mathematicae Applicatae Sinica》 SCIE CSCD 2019年第3期491-512,共22页 应用数学学报(英文版)
基金 supported by National Natural Science Foundation of China(No.11301084) Natural Science Foundation of Fujian Province,China(No.2014J01010)
关键词 NONPARAMETRIC M-estimator FUNCTIONAL STATIONARY ERGODIC DATA weak consistency asymptotic normality nonparametric M-estimator functional stationary ergodic data weak consistency asymptotic normality
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