Linear Regression Analysis for Symbolic Interval Data  

作　　者：Jin-Jian Hsieh Chien-Cheng Pan 

机构地区：[1]Department of Mathematics, National Chung Cheng University, Taiwan

出　　处：《Open Journal of Statistics》2018年第6期885-901,共17页统计学期刊（英文）

摘　　要：In the network technology era, the collected data are growing more and more complex, and become larger than before. In this article, we focus on estimates of the linear regression parameters for symbolic interval data. We propose two approaches to estimate regression parameters for symbolic interval data under two different data models and compare our proposed approaches with the existing methods via simulations. Finally, we analyze two real datasets with the proposed methods for illustrations.In the network technology era, the collected data are growing more and more complex, and become larger than before. In this article, we focus on estimates of the linear regression parameters for symbolic interval data. We propose two approaches to estimate regression parameters for symbolic interval data under two different data models and compare our proposed approaches with the existing methods via simulations. Finally, we analyze two real datasets with the proposed methods for illustrations.

关 键 词：LINEAR Regression SYMBOLIC INTERVAL Data CENTRE Method Least SQUARES ESTIMATE 

分 类 号：O1[理学—数学]