An improved grey relational analysis approach for panel data clustering
作者：
Highlights：
• Our method can handle different lengths of time series within a sample and across samples.
• The new method is useful when values occur at different times when comparing any two series.
• The new clustering method avoids the problem of combining two samples having a limited degree of similarity.
• If the order of the indicators and samples changes, the results are the same.
• The provinces in China can be meaningfully categorized according to ecological environment.
摘要
•Our method can handle different lengths of time series within a sample and across samples.•The new method is useful when values occur at different times when comparing any two series.•The new clustering method avoids the problem of combining two samples having a limited degree of similarity.•If the order of the indicators and samples changes, the results are the same.•The provinces in China can be meaningfully categorized according to ecological environment.
论文关键词：Clustering,Panel data,Grey relational analysis,Chinese panel data
论文评审过程：Received 11 August 2014, Revised 24 July 2015, Accepted 27 July 2015, Available online 7 August 2015, Version of Record 2 September 2015.
论文官网地址：https://doi.org/10.1016/j.eswa.2015.07.066
