admissibility in a one parameter non-regular family with squared-log error loss function

Authors

shirin moradi zahraie

hojatollah zakerzadeh

abstract

‎consider an estimation problem in a one-parameter non-regular distribution when both endpoints of the support depend on a single parameter‎. ‎in this paper‎, ‎we give sufficient conditions for a generalized bayes estimator of a parametric function to be admissible‎. ‎some examples are given‎. ‎

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

Admissibility in a One Parameter Non-regular Family with Squared-log Error Loss Function

‎Consider an estimation problem in a one-parameter non-regular distribution when both endpoints of the support depend on a single parameter‎. ‎In this paper‎, ‎we give sufficient conditions for a generalized Bayes estimator of a parametric function to be admissible‎. ‎Some examples are given‎. ‎

full text

Minimax Estimator of a Lower Bounded Parameter of a Discrete Distribution under a Squared Log Error Loss Function

The problem of estimating the parameter ?, when it is restricted to an interval of the form , in a class of discrete distributions, including Binomial Negative Binomial discrete Weibull and etc., is considered. We give necessary and sufficient conditions for which the Bayes estimator of with respect to a two points boundary supported prior is minimax under squared log error loss function....

full text

Admissible and Minimax Estimator of the Parameter $theta$ in a Binomial $Bin( n ,theta)$ ­distribution under Squared Log Error Loss Function in a Lower Bounded Parameter Space

Extended Abstract. The study of truncated parameter space in general is of interest for the following reasons: 1.They often occur in practice. In many cases certain parameter values can be excluded from the parameter space. Nearly all problems in practice have a truncated parameter space and it is most impossible to argue in practice that a parameter is not bounded. In truncated parameter...

full text

minimax estimator of a lower bounded parameter of a discrete distribution under a squared log error loss function

the problem of estimating the parameter ?, when it is restricted to an interval of the form , in a class of discrete distributions, including binomial negative binomial discrete weibull and etc., is considered. we give necessary and sufficient conditions for which the bayes estimator of with respect to a two points boundary supported prior is minimax under squared log error loss function. for s...

full text

Minimax Estimation of the Scale Parameter in a Family of Transformed Chi-Square Distributions under Asymmetric Squared Log Error and MLINEX Loss Functions

This paper is concerned with the problem of finding the minimax estimators of the scale parameter ? in a family of transformed chi-square distributions, under asymmetric squared log error (SLE) and modified linear exponential (MLINEX) loss functions, using the Lehmann Theorem [2]. Also we show that the results of Podder et al. [4] for Pareto distribution are a special case of our results for th...

full text

An Admissible Estimator of a Lower-bounded Scale Parameter under Squared-log Error Loss Function

Estimation in truncated parameter space is one of the most important features in statistical inference, because the frequently used criterion of unbiasedness is useless, since no unbiased estimator exists in general. So, other optimally criteria such as admissibility and minimaxity have to be looked for among others. In this paper we consider a subclass of the exponential families of distributi...

full text

My Resources

Save resource for easier access later


Journal title:
journal of the iranian statistical society

جلد ۱۶، شماره ۱، صفحات ۱۹-۳۱

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023