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Analysis method for linear regression model with unequally spaced autoregression series error

  • Xiaobing Ma*
  • , Shihua Chang
  • *Corresponding author for this work
  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The analysis method for regression model with unequally spaced time series error is presented, which is based on the relationship between the Green function of continuous system and the autoregression parameters of the time series. The conditional maximum likelihood estimation and exact maximum likelihood estimation of parameters of the regression model with unequally spaced correlated error are discussed in detail. The method is not only suitable for the time series with missing observations but also applicable to the irregularly sampled data in social and natural science. The method can also combine regression with autoregression and promote the precision of analysis and forecast. Numerical examples are given at last, which can illustrate the performance of the new method.

Original languageEnglish
Title of host publication2011 Prognostics and System Health Management Conference, PHM-Shenzhen 2011
DOIs
StatePublished - 2011
Event2011 Prognostics and System Health Management Conference, PHM-Shenzhen 2011 - Shenzhen, China
Duration: 24 May 201125 May 2011

Publication series

Name2011 Prognostics and System Health Management Conference, PHM-Shenzhen 2011

Conference

Conference2011 Prognostics and System Health Management Conference, PHM-Shenzhen 2011
Country/TerritoryChina
CityShenzhen
Period24/05/1125/05/11

Keywords

  • Linear regression model
  • Maximum likelihood estimation
  • Missing observation
  • Time series
  • Unequally spaced data

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