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Modeling and Statistical Inference on Generalized Inverse Weibull Software Reliability Growth Model

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Abstract

In this paper we introduce the generalized inverse Weibull finite failure software reliability model which includes both increasing and decreasing nature of the hazard function. The increasing/decreasing behaviour of the failure occurrence rate fault is taken into account by the hazard of generalized inverse Weibull distribution. The model parameters are estimated using maximum likelihood method for interval domain data and numerical examples are provided to illustrate the estimation technique. The proposed model is compared with the standard existing models through error sum of squares, mean sum of squares, predictive ratio risk and Akaikes information criteria using different data sets. The result showed that the proposed model performs satisfactorily better than the existing finite failure category models.

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Correspondence to David D. Hanagal.

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Hanagal, D.D., Bhalerao, N.N. Modeling and Statistical Inference on Generalized Inverse Weibull Software Reliability Growth Model. J Indian Soc Probab Stat 17, 145–160 (2016). https://doi.org/10.1007/s41096-016-0010-8

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