文章基本信息

标题：Nonparametric Estimation with Aggregated Data
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作者：Oliver Linton ; Yoon-Jae Whang
期刊名称：Distributional Analysis Publications
印刷版ISSN：1352-2469
出版年度：2000
卷号：2000
出版社：Suntory Toyota International Centres for Economics and Related Disciplines
摘要：We introduce a kernel-based estimator of the density function and regression function for data that have been grouped into family totals. We allow for a common intra-family component but require that observations from different families be in dependent. We establish consistency and asymptotic normality for our procedures. As usual, the rates of convergence can be very slow depending on the behaviour of the characteristic function at infinity. We investigate the practical performance of our method in a simple Monte Carlo experiment
关键词：Aggregated data; deconvolution; grouped data; kernel; ;nonparametric regression