Poisson regression models of infrastructure transition probabilities

Samer Madanat, Wan Hashim Wan Ibrahim

Research output: Contribution to journalArticle

Abstract

Markovian transition probabilities have been used extensively in the field of infrastructure management, to provide forecasts of facility conditions. However, existing approaches used to estimate these transition probabilities from inspection data are mostly ad hoc and suffer from several statistical limitations. In this paper, econometric methods for the estimation of infrastructure deterioration models and associated transition probabilities from inspection data are presented. The first method is based on the Poisson regression model and follows directly from the Markovian behavior of infrastructure deterioration. The negative binomial regression, a generalization of the Poisson model that relaxes the assumption of equality of mean and variance, is also presented. An empirical case study, using a bridge inspection data set from Indiana, demonstrates the capabilities of the two methods.

Original languageEnglish (US)
Pages (from-to)267-272
Number of pages6
JournalJournal of Transportation Engineering
Volume121
Issue number3
DOIs
StatePublished - May 1995

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Transportation

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