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Original Articles

Estimation of reliability of multicomponent stress–strength for a Kumaraswamy distribution

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Pages 1560-1572 | Received 27 May 2014, Accepted 10 Feb 2015, Published online: 08 Mar 2016

References

  • Bhattacharya, D., Roychowdhury, S. (2013). Reliability of a coherent system in a multicomponent stress-strength model. Am. J. Math. Manage. Sci. 32(1):40–52.
  • Bhattacharyya, G.K., Johnson, R.A. (1974). Estimation of reliability in a multicomponent stress-strength mode. J. Am. Stat. Assoc. 69(348):966–970.
  • Chib, S., Greenberg, E. (1995). Understanding the Metropolis-Hastings algorithm. Am. Stat. 49(4):327–335.
  • Congdon, P. (2001). Bayesian Statistical Modeling. New York: John Wiley.
  • Courard-Hauri, D. (2007). Using Monte Carlo analysis to investigate the relationship between overconsumption and uncertain access to one’s personal utility function. Ecol. Econ. 64(1):152–162.
  • Dasgupta, R. (2011). On the distribution of Burr with applications. Sankhya B 73(1):1–19.
  • Draper, N.R., Guttman, I. (1978). Bayesian analysis of reliability in multicomponent stress-strength models. Commun. Stat. Theory Methods 7(5):441–451.
  • Ebrahimi, N. (1982). Estimation of reliability for a series stress-strength system. IEEE Trans. Reliab. 31(2):202–205.
  • Fletcher, S.G., Ponnambalam, K. (1996). Estimation of reservoir yield and storage distribution using moments analysis. J. Hydrol. 182(1–4):259–275.
  • Ganji, A., Ponnambalam, K., Khalili, D., Karamouz, M. (2006). Grain yield reliability analysis with crop water demand uncertainty. Stochastic Environ. Res. Risk Assess. (SERRA) 20(4):259–277.
  • Garg, M. (2008). On distribution of order statistics from Kumaraswamy distribution. Kyungpook Math. J. 48(3):411–417.
  • Garg, M. (2009). On generalized order statistics from Kumaraswamy distribution. Tamsui Oxford J. Math. Sci. 25(2):153–166.
  • Gholizadeh, R., Khalilpor, M., Hadian, M. (2011). Bayesian estimations in the Kumaraswamy distribution under progressively type II censoring data. Int. J. Eng. Sci. Technol. 9(9):47–65.
  • Hanagal, D. (2003). Estimation of system reliability in multicomponent series stress-strength models. J. Indian Stat. Assoc. 41(1):1–7.
  • Hassan, A.S., Basheikh, H.M. (2012). Reliability estimation of stress-strength model with non-identical component strengths: the exponentiated Pareto case. Int. J. Eng. Res. Appl. 2(3):2774–2781.
  • Heidelberger, P., Welch, P.D. (1981). A spectral method for confidence interval generation and run length control in simulations. Commun. Assoc. Comput. Mach. 24(4):233–245.
  • Heidelberger, P., Welch, P.D. (1983). Simulation run length control in the presence of an initial transient. Oper. Res. 31(6):1109–1144.
  • Jones, M.C. (2009). Kumaraswamy’s distribution: a beta-type distribution with some tractability advantages. Stat. Methodol. 6(1):70–81.
  • Kotz, S., Lumelskii, Y., Pensky, M. (2003). The Stress-Strength Model and Its Generalizations. Singapore: World Scientific.
  • Kumaraswamy, P. (1980). A generalized probability density function for double-bounded random processes. J. Hydrol. 46(1–2):79–88.
  • Kundu, D., Gupta, R.D. (2005). Estimation of P[Y < X] for generalized exponential distribution. Metrika 61(3):291–308.
  • Lemonte, A.J. (2011). Improved point estimation for the Kumaraswamy distribution. J. Stat. Comput. Simul. 81(12):1971–1982.
  • Mitnik, P.A. (2013). New properties of the Kumaraswamy distribution. Commun. Stat. - Theory Methods 42(5):741–755.
  • Nadar, M., Kizilaslan, F. (2014). Classical and Bayesian estimation of P(X<Y) using upper record values from Kumaraswamy’s distribution. Stat. Pap. 55(3):751–783.
  • Nadar, M., Kizilaslan, F., Papadopoulos, A. (2014). Classical and Bayesian estimation of P(Y<X) for Kumaraswamy’s distribution. J. Stat. Comput. Simul. 84(7):1505–1529.
  • Nadar, M., Papadopoulos, A., Kizilaslan, F. (2013). Statistical analysis for Kumaraswamy’s distribution based on record data. Stat. Pap. 54(2):355–369.
  • Pandey, M., BorhanUddin, M.B. (1992). Reliability estimation of an s-out-of-k system with non-identical component strengths: the Weibull case. Reliab. Eng. Syst. Saf. 36(2):109–116.
  • Paul, P.K., BorhanUddin, M.B. (1997). Estimation of reliability of stress-strength model with non-identical component strengths. Microelectron. Reliab. 37(6):923–927.
  • R Development Core Team., (2011). R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing.
  • Rao, C.R., Toutenburg, H. (1999). Linear Models, 2nd Edition. Springer Series in Statistics. New York: Springer-Verlag.
  • Rao, G.S. (2012a). Estimation of reliability in multicomponent stress-strength based on generalized exponential distribution. Revista Colombiana de Estadistica 35:67–76.
  • Rao, G.S. (2012b). Estimation of reliability in multicomponent stress-strength based on generalized inverted exponential distribution. Int. J. Curr. Res. Rev. 4(21):48–56.
  • Rao, G.S. (2012c). Estimation of reliability in multicomponent stress-strength model based on Rayleigh distribution. ProbStat Forum 5:150–161.
  • Rao, G.S., Kantam, R.R.L. (2010). Estimation of reliability in multicomponent stress-strength model: log-logistic distribution. J. Appl. Stat. Sci. 3(2):75–84.
  • Sánchez, S., Ancheyta, J., McCaffrey, W.C. (2007). Comparison of probability distribution functions for fitting distillation curves of petroleum. Energy Fuels 21(5):2955–2963.
  • SAS., (2010a). The MCMC Procedure, SAS/STAT® User’s Guide, Version 9.22. Cary, NC: SAS Institute Inc.
  • SAS., (2010b). The NLMIXED Procedure, SAS/STAT® User’s Guide, Version 9.22. Cary, NC: SAS Institute Inc.
  • Seifi, A., Ponnambalam, K., Vlach, J. (2000). Maximization of manufacturing yield of systems with arbitrary distributions of component values. Ann. Oper. Res. 99:373–383.
  • Serkan, E. (2008a). Consecutive k-out-of n: G system in stress-strength setup. Commun. Stat. - Simul. Comput. 37(3–5):579–589.
  • Serkan, E. (2008b). Multivariate stress-strength reliability model and its evaluation for coherent structures. J. Multivariate Anal. 99(9):1878–1887.
  • Serkan, E., Funda, I. (2011). Reliability evaluation for a multi-state system under stress-strength setup. Commun. Stat. - Theory Methods 40(3):547–558.
  • Sindhu, T.N., Feroze, N., Aslam, M. (2013). Bayesian analysis of the Kumaraswamy distribution under failure censoring sampling scheme. Int. J. Adv. Sci. Technol. 51(51):39–58.
  • Sundar, V., Subbiah, K. (1989). Application of double bounded probability density function for analysis of ocean waves. Ocean Eng. 16(2):193–200.
  • Turkkan, N., Pham-Gia, T. (2007). System stress-strength reliability: the multivariate case. IEEE Trans. Reliab. 56(1):115–124.

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