A resampling approach for interval-valued data regression

Jeongyoun Ahn, Muliang Peng, Cheolwoo Park, Yongho Jeon

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)


We consider interval-valued data that frequently appear with advanced technologies in current data collection processes. Interval-valued data refer to the data that are observed as ranges instead of single values. In the last decade, several approaches to the regression analysis of interval-valued data have been introduced, but little work has been done on relevant statistical inferences concerning the regression model. In this paper, we propose a new approach to fit a linear regression model to interval-valued data using a resampling idea. A key advantage is that it enables one to make inferences on the model such as the overall model significance test and individual coefficient test. We demonstrate the proposed approach using simulated and real data examples, and also compare its performance with those of existing methods.

Original languageEnglish
Pages (from-to)336-348
Number of pages13
JournalStatistical Analysis and Data Mining
Issue number4
Publication statusPublished - 2012 Aug

All Science Journal Classification (ASJC) codes

  • Analysis
  • Information Systems
  • Computer Science Applications


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