Parameter Estimation of Weighted New Weibull Pareto Distribution

Authors

Sofi Mudasir
Department of Statistics, University of Kashmir, Srinagar, India
S P Ahmad
Department of Statistics, University of Kashmir, Srinagar, India

Synopsis

In this chapter, method of moments, maximum likelihood and Bayesian methods of estimation were studied for estimating the scale parameter of the WNWP distribution. Bayes estimators are obtained using different loss functions under different types of priors. For comparison of different loss functions and different types of priors, two real life data sets are used, and the outcomes are obtained through R-software. On equating the posterior risk obtained under different loss functions, it is clear from the above tables that QLF has minimum value of posterior risk and is thus preferable as compared to other loss functions used in this paper. Also, from tables 2.2 to 2.7, it is clear that in order to estimate the said parameter combination of quadratic loss function and extension of Jeffrey’s prior can be preferred.

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Published
March 26, 2019