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Semi-parametric proportional intensity models robustness for right-censored recurrent failure data

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  • Jiang, S.T.
  • Landers, T.L.
  • Rhoads, T.R.

Abstract

This paper reports the robustness of the four proportional intensity (PI) models: Prentice–Williams–Peterson-gap time (PWP-GT), PWP-total time (PWP-TT), Andersen–Gill (AG), and Wei–Lin–Weissfeld (WLW), for right-censored recurrent failure event data. The results are beneficial to practitioners in anticipating the more favorable engineering application domains and selecting appropriate PI models. The PWP-GT and AG prove to be models of choice over ranges of sample sizes, shape parameters, and censoring severity. At the smaller sample size (U=60), where there are 30 per class for a two-level covariate, the PWP-GT proves to perform well for moderate right-censoring (Pc≤0.8), where 80% of the units have some censoring, and moderately decreasing, constant, and moderately increasing rates of occurrence of failures (power-law NHPP shape parameter in the range of 0.8≤δ≤1.8). For the large sample size (U=180), the PWP-GT performs well for severe right-censoring (0.8

Suggested Citation

  • Jiang, S.T. & Landers, T.L. & Rhoads, T.R., 2005. "Semi-parametric proportional intensity models robustness for right-censored recurrent failure data," Reliability Engineering and System Safety, Elsevier, vol. 90(1), pages 91-98.
    • Handle: RePEc:eee:reensy:v:90:y:2005:i:1:p:91-98
    DOI: 10.1016/j.ress.2004.11.017
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    References listed on IDEAS

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    1. J Ansell & T Archibald & J Dagpunar & L Thomas & P Abell & D Duncalf, 2003. "Analysing maintenance data to gain insight into systems performance," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(4), pages 343-349, April.
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    Cited by:

    1. Kappen, Philip, 2011. "Competence-creating overlaps and subsidiary technological evolution in the multinational corporation," Research Policy, Elsevier, vol. 40(5), pages 673-686, June.
    2. Regattieri, A. & Manzini, R. & Battini, D., 2010. "Estimating reliability characteristics in the presence of censored data: A case study in a light commercial vehicle manufacturing system," Reliability Engineering and System Safety, Elsevier, vol. 95(10), pages 1093-1102.
    3. Babykina, Génia & Couallier, Vincent, 2012. "Empirical assessment of the Maximum Likelihood Estimator quality in a parametric counting process model for recurrent events," Computational Statistics & Data Analysis, Elsevier, vol. 56(2), pages 297-315.

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