[PDF][PDF] Bayesian analysis of lomax distribution under asymmetric loss functions
Journal of Statistics Applications and Probability Letters, 2016•naturalspublishing.com
In the present paper, a two parametric Lomax distribution is considered for Bayesian
analysis. The estimation of the shape parameter of Lomax distribution is obtained by
employing the classical and Bayesian paradigm. Bayes' estimators are obtained by using
extension of Jeffrey's prior and Gamma prior under Entropy loss function and Precautionary
loss function. Maximum likelihood estimation is also discussed. These methods are
compared by using mean square error through simulation study with varying sample sizes.
analysis. The estimation of the shape parameter of Lomax distribution is obtained by
employing the classical and Bayesian paradigm. Bayes' estimators are obtained by using
extension of Jeffrey's prior and Gamma prior under Entropy loss function and Precautionary
loss function. Maximum likelihood estimation is also discussed. These methods are
compared by using mean square error through simulation study with varying sample sizes.
Abstract
In the present paper, a two parametric Lomax distribution is considered for Bayesian analysis. The estimation of the shape parameter of Lomax distribution is obtained by employing the classical and Bayesian paradigm. Bayes’ estimators are obtained by using extension of Jeffrey’s prior and Gamma prior under Entropy loss function and Precautionary loss function. Maximum likelihood estimation is also discussed. These methods are compared by using mean square error through simulation study with varying sample sizes.
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