BAYES ESTIMATION USING A LINEX LOSS FUNCTION
Authors: not saved
Abstract:
This paper considers estimation of normal mean ? when the variance is unknown, using the LINEX loss function. The unique Bayes estimate of ? is obtained when the precision parameter has an Inverse Gaussian prior density
similar resources
Bayes, E-Bayes and Robust Bayes Premium Estimation and Prediction under the Squared Log Error Loss Function
In risk analysis based on Bayesian framework, premium calculation requires specification of a prior distribution for the risk parameter in the heterogeneous portfolio. When the prior knowledge is vague, the E-Bayesian and robust Bayesian analysis can be used to handle the uncertainty in specifying the prior distribution by considering a class of priors instead of a single prior. In th...
full textEstimating a Bounded Normal Mean Under the LINEX Loss Function
Let X be a random variable from a normal distribution with unknown mean θ and known variance σ2. In many practical situations, θ is known in advance to lie in an interval, say [−m,m], for some m > 0. As the usual estimator of θ, i.e., X under the LINEX loss function is inadmissible, finding some competitors for X becomes worthwhile. The only study in the literature considered the problem of min...
full textBayesian Estimation for the Pareto Income Distribution under Asymmetric LINEX Loss Function
The use of the Pareto distribution as a model for various socio-economic phenomena dates back to the late nineteenth century. In this paper, after some necessary preliminary results we deal with Bayes estimation of some of the parameters of interest under an asymmetric LINEX loss function, using suitable choice of priors when the scale parameter is known and unknown. Results of a Monte C...
full textMonotone Empirical Bayes Test for a Truncation Parameter Distribution Using Linex Loss
This paper deals with a monotone empirical Bayes test δ∗ n for a truncation parameter distribution using the linex loss. The asymptotic optimality of δ∗ n is investigated. Under very mild conditions, it is shown that δ∗ n is asymptotically optimal with a rate of order n. This rate improves the empirical Bayes test δ n of Xu and Shi (2004) in the sense that faster convergence rate is achieved un...
full textEmpirical Bayes estimators of reliability performances using LINEX loss under progressively Type-II censored samples
Based on progressively Type-II censored samples, the empirical estimators of reliability performances for Burr XII distribution are researched under LINEX error loss. Firstly, we obtain the Bayes estimators of the reliability performances. Secondly, different from the predecessor, the empirical Bayes estimators of the reliability performances are derived where hyper-parameter is estimated using...
full textEstimating a Bounded Normal Mean Under the LINEX Loss Function
Let X be a random variable from a normal distribution with unknown mean θ and known variance σ2. In many practical situations, θ is known in advance to lie in an interval, say [−m,m], for some m > 0. As the usual estimator of θ, i.e., X under the LINEX loss function is inadmissible, finding some competitors for X becomes worthwhile. The only study in the literature considered the problem of min...
full textMy Resources
Journal title
volume 1 issue 4
pages -
publication date 1990-08-01
By following a journal you will be notified via email when a new issue of this journal is published.
Hosted on Doprax cloud platform doprax.com
copyright © 2015-2023