Parameter and reliability estimation of three-parameter lifetime distributions for fuzzy life times

Besides errors and stochastic variation, the observed data always have more or less imprecision. In contrast, classical statistical procedures are based on precise measurements and do not allow imprecision of the individual observations. Therefore, to integrate imprecision of the observations, classical statistical techniques are required to generalize for fuzzy numbers. Since lifetime measurements are also more or less fuzzy, therefore, this study was aimed to generalize parameters and reliability functions estimation for the three-parameter lifetime distributions in such manners to integrate fuzziness of the lifetime data. The obtained estimators assimilate fuzziness and stochastic variation of lifetime observations, whereas classical techniques are only based on stochastic variation. This propagation of fuzziness makes the proposed estimators more realistic and suitable for lifetime analysis. Therefore, in order to model lifetime data, the suggested techniques are far better alternative.

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