A resampling approach for interval-valued data regression

Jeongyoun Ahn, Muliang Peng, Cheolwoo Park, Yongho Jeon

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

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
Volume5
Issue number4
DOIs
Publication statusPublished - 2012 Aug 1

Fingerprint

Resampling
Regression
Interval
Linear regression
Regression analysis
Significance Test
Linear Regression Model
Statistical Inference
Regression Analysis
Regression Model
Coefficient
Model
Range of data
Demonstrate

All Science Journal Classification (ASJC) codes

  • Analysis
  • Information Systems
  • Computer Science Applications

Cite this

Ahn, Jeongyoun ; Peng, Muliang ; Park, Cheolwoo ; Jeon, Yongho. / A resampling approach for interval-valued data regression. In: Statistical Analysis and Data Mining. 2012 ; Vol. 5, No. 4. pp. 336-348.
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A resampling approach for interval-valued data regression. / Ahn, Jeongyoun; Peng, Muliang; Park, Cheolwoo; Jeon, Yongho.

In: Statistical Analysis and Data Mining, Vol. 5, No. 4, 01.08.2012, p. 336-348.

Research output: Contribution to journalArticle

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