‎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. ‎

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...

the log damage and value loss were examined by felling and bucking function, species, and damage type, in kheyrud forest in namkhaneh district in the hyrcanian forest of iran. in order to calculate the wood value following tree felling and bucking, 250 trees and 167 logs consisting of beech and hornbeam species were measured. there were five types of damage recorded following the tree felling o...

‎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. ‎

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...

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....

We consider the problem of estimating the transition probability kernel to be used by a model-based reinforcement learning (RL) algorithm. We argue that estimating a generative model that minimizes a probabilistic loss, such as the log-loss, might be an overkill because such a probabilistic loss does not take into account the underlying structure of the decision problem and the RL algorithm tha...

test day milk records of a holstein dairy farm collected during years 2004 to 2006 on 142 cows in the 1st lactation vs. 140 cows in the 2nd lactation were used in this research. there were real milk yields of cows available in each part of lactation in this farm making it possible to compare functions based on the new criteria (squared error of estimation). five functions were compared to estim...