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 - Jan 1 1995

    Fingerprint

    Inspection
    infrastructure
    regression
    Deterioration
    econometrics
    equality
    management

    ASJC Scopus subject areas

    • Civil and Structural Engineering
    • Transportation

    Cite this

    Poisson regression models of infrastructure transition probabilities. / Madanat, Samer; Wan Ibrahim, Wan Hashim.

    In: Journal of Transportation Engineering, Vol. 121, No. 3, 01.01.1995, p. 267-272.

    Research output: Contribution to journalArticle

    Madanat, Samer ; Wan Ibrahim, Wan Hashim. / Poisson regression models of infrastructure transition probabilities. In: Journal of Transportation Engineering. 1995 ; Vol. 121, No. 3. pp. 267-272.
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