A generalized log-normal distribution and its goodness of fit to censored data. (English) Zbl 1304.65073
Summary: In life testing experiments, the skewed distributions like log-normal, Weibull, gamma and generalized gamma are the most suitable models for recording the failure time measurements. In this paper, a generalized version of log-normal distribution is proposed and its goodness-of-fit for a randomly censored data set representing the remission times of bladder cancer patients has been demonstrated and compared with other lifetime models considered in the literature. The P-P plots of Kaplan-Meier estimator against the survival functions of the considered models are used to show the goodness-of-fit. A simulation study is also performed to estimate the parameters in both the classical and Bayesian setups.
MSC:
| 62-08 | Computational methods for problems pertaining to statistics |
Keywords:
maximum likelihood estimator; Bayes estimator; squared error loss function; Kaplan-Meier estimator; Markov chain Monte Carlo; Gibbs sampler; highest posterior density intervalsReferences:
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