Modeling repairable system failures with repair effect and time dependent covariates.

In this paper we extend a repairable system model that incorporates both time trend and repair history to include a time dependent covariate. We calculated the bias, standard error and RMSE of the parameter estimates of this model at different sample sizes using simulated data. Following that, we studied the Wald method of constructing confidence interval estimates for the parameters of this model. Finally the model is fit to real data from the pipeline network failure.

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