Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30184
Analyzing the Factors Effecting the Passenger Car Breakdowns using Com-Poisson GLM

Authors: N. Mamode Khan, V. Jowaheer

Abstract:

Number of breakdowns experienced by a machinery is a highly under-dispersed count random variable and its value can be attributed to the factors related to the mechanical input and output of that machinery. Analyzing such under-dispersed count observations as a function of the explanatory factors has been a challenging problem. In this paper, we aim at estimating the effects of various factors on the number of breakdowns experienced by a passenger car based on a study performed in Mauritius over a year. We remark that the number of passenger car breakdowns is highly under-dispersed. These data are therefore modelled and analyzed using Com-Poisson regression model. We use quasi-likelihood estimation approach to estimate the parameters of the model. Under-dispersion parameter is estimated to be 2.14 justifying the appropriateness of Com-Poisson distribution in modelling under-dispersed count responses recorded in this study.

Keywords: Breakdowns, under-dispersion, com-poisson, generalized linear model, quasi-likelihood estimation

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1060441

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1239

References:


[1] S. Guikema, " Formulating informative data -based priors for failure probability estimation in reliability analysis", Reliability Engineering and System Safety, Vol 92, 490-502,2007.
[2] V. Jowaheer and N. Mamode Khan, " Estimating Regression Effects in Com-Poisson Generalized Linear Model", International Journal of Mathematical and Statistical Sciences, Vol 1:2, 2009
[3] J. Kadane , G. Shmueli, G. Minka, T. Borle and P. Boatwright, " Conjugate analysis of the Conway Maxwell Poisson distribution", Bayesian analysis, Vol 1, 363-374,2006.
[4] D. Lord,.S Guikema, and S. Geedipally "Application of the Conway- Maxwell-Poisson Generalized Linear Model for Analyzing Motor Vehicle Crashes". Accident Analysis and Prevention, Vol. 40, 1123-1134,2008
[5] G. Shmueli, T. Minka, J. Borle and P. Boatwright, " A useful distribution for fitting discrete data, Journal of Royal Statistical Society, 2005.
[6] Road accidents in Mauritius: statistics and analysis http : //www.gov.mu/portal/goc/mpi/file/roadsafety.pdf, Last access: 12.10.2009
[7] RAC patrol report in UK: http : //www.rac.co.uk/press−centre/, Last access: 19.10.2009