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Minimax Estimation of the Bounded Parameter of Some Discrete Distributions Under LINEX Loss Function

机译:LINEX损失函数下某些离散分布的有界参数的极小极大估计

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摘要

For a class of discrete distributions, including Poisson(θ), Generalized Poisson(θ), Borel(m, θ), etc., we consider minimax estimation of the parameter θ under the assumption it lies in a bounded interval of the form [0, m] and a LINEX loss function. Explicit conditions for the minimax estimator to be Bayes with respect to a boundary supported prior are given. Also for Bernoulli(d)-distribution, which is not in the mentioned class of discrete distributions, we give conditions for which the Bayes estimator of θ € [0, m], m < 1 with respect to a boundary supported prior is minimax under LINEX loss function. Numerical values are given for the largest values of m for which the corresponding Bayes estimators of θ are minimax.
机译:对于包括Poisson(θ),广义Poisson(θ),Borel(m,θ)等在内的一类离散分布,我们考虑参数θ的极小极大估计,假设它位于[ 0,m]和LINEX损失函数。给出了极小极大估计量相对于先验支持边界的贝叶斯的显式条件。同样,对于不在提到的离散分布类别中的伯努利(d)分布,我们给出条件,在该条件下,相对于先验支持边界的θ€[0,m],m <1的Bayes估计LINEX损失功能。给出了m的最大值的数值,其对应的θ贝叶斯估计量为maxmax。

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