Log-logistic Distribution as a Reliability Model: A Bayesian Analysis
نویسندگان
چکیده
Log-logistic distribution is a very important reliability model as it fits well in many practical situations of reliability data analyses. Another important feature with the log-logistic distribution lies in its closed form expression for survival and hazard functions that makes it advantageous over log-normal distribution. It is therefore more convenient in handling censored data than the log-normal, while providing a good approximation to it except in the extreme tails. In this paper an attempt has been made to use Bayesian analytic and simulation methods for fitting the log-logistic reliability model. Real datasets are used for the purpose of illustrations. R code has been provided to implement in censored mechanism. Laplace approximation is implemented for approximating posterior densities of the parameters. Moreover, parallel simulation tools are also implemented with an extensive use of R.
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