TECHNICAL PAPERS
May 1, 1995

Poisson Regression Models of Infrastructure Transition Probabilities

Publication: Journal of Transportation Engineering
Volume 121, Issue 3

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.

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Go to Journal of Transportation Engineering
Journal of Transportation Engineering
Volume 121Issue 3May 1995
Pages: 267 - 272

History

Published online: May 1, 1995
Published in print: May 1995

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Authors

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Samer Madanat
Asst. Prof., School of Civ. Engrg., Purdue Univ., West Lafayette, IN 47907.
Wan Hashim Wan Ibrahim
Grad. Res. Asst., School of Civ. Engrg., Purdue Univ., West Lafayette, IN.

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