In this paper, Bayes estimators of parameter of Maxwell distribution have been derived by considering non-informative as well as conjugate priors under different scale invariant loss functions, namely, Quadratic Loss Function, Squared-Log Error Loss Function and Modified Linear Exponential Loss Function. The risk functions of these estimators have been studied.
AMS Subject Classification
Maxwell distribution Conjugate prior MLINEX loss function Non-informative prior Posterior density Quadratic loss function Risk function Squared-log error loss function
This is a preview of subscription content, log in to check access.
Awad, A.M., Gharraf, M.K., 1986. Estimation of P[Y < X] in the Burr case: A comparative study. Communications in Statistics — Simulation and Computation, 15, 189–203.MathSciNetzbMATHGoogle Scholar
Bekker, A., Roux, J.J.J., 2005. Reliability Characteristics of the Maxwell Distribution: A Bayes Estimation Study. Communications in Statistics — Theory and Methods, 34, 2169–2178.MathSciNetCrossRefGoogle Scholar
Brown, L.D., 1968. Inadmissibility of the usual estimators of scale parameters in problems with unknown location and scale parameters. Annals of Mathematical Statistics, 39, 29–48.MathSciNetCrossRefGoogle Scholar
Chaturvedi, A., Rani, U., 1998. Classical and Bayesian Reliability estimation of the generalized Maxwell failure distribution. Journal of Statistical Research, 32, 113–120.MathSciNetGoogle Scholar