文章基本信息

标题：Efficient Estimation of Interval-Valued Symbolic Data Regression Model
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作者：Chuanhua Wei ; Nana Zheng ; Ke Tian 等
期刊名称：International Journal of Statistics and Probability
印刷版ISSN：1927-7032
电子版ISSN：1927-7040
出版年度：2020
卷号：9
期号：2
页码：1-6
DOI：10.5539/ijsp.v9n2p1
语种：English
出版社：Canadian Center of Science and Education
摘要：In the last two decades, regression analysis with interval-valued type data has received more and more attention. For the interval-valued symbolic data regression, the Minmax method and the center and range (CR) method are two widely used popular estimating approaches. In this paper, to improve the estimating eciency of these two estimating methods, seemingly unrelated regression approach has been applied to take account of the dependence information of two regression models of the Minmax method or the CR method. Finally, real data sets are analysed to examine the performance of our proposed procedure.
关键词：interval-valued data; minmax method; center and range method; seemingly unrelated regression; generalized least squares estimation