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    政大機構典藏 > 理學院 > 應用數學系 > 期刊論文 >  Item 140.119/18681
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/18681

    Title: Kernel density estimation under weak dependence with sampled data
    Authors: 吳柏林
    Wu, Berlin
    Date: 1997-05
    Issue Date: 2008-12-24 13:28:45 (UTC+8)
    Abstract: Kernel type estimators of the density of continuous time
    d-valued stochastic processes are studied. Uniform strong consistency on
    d of the estimators and their rates of convergence are obtained. The stochastic processes are assumed to satisfy the strong mixing condition and the sampling instants are random. It is shown that the estimators can attain the optimal L2 rates of convergence.
    Relation: Journal of Statistical Planning and Inference,61,141-154
    Data Type: article
    DOI 連結: https://doi.org/10.1016/S0378-3758(96)00151-6
    DOI: 10.1016/S0378-3758(96)00151-6
    Appears in Collections:[應用數學系] 期刊論文

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