具有一系列随机约束的广义Liu估计的初步检验

IF 0.1 Q4 STATISTICS & PROBABILITY

JIRSS-Journal of the Iranian Statistical Society Pub Date : 2019-06-01 DOI:10.29252/JIRSS.18.1.113

M. Karbalaee, S. M. M. Tabatabaey, M. Arashi

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引用次数: 7

摘要

在存在一系列随机约束条件的情况下，研究了基于Wald、似然比和拉格朗日乘子检验的初步检验广义Liu估计的性能。在均方误差意义下，得到了偏置参数的最优范围。为此，使用偏置矩阵分量的最小/最大值来给出适当的最优范围，其中偏置矩阵为D = diag(d1, d2，…)。， dp)， 0 < di < 1, I = 1，…我们用一些数值实例来支持我们的发现。

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On the Preliminary Test Generalized Liu Estimator with Series of Stochastic Restrictions

When a series of stochastic restrictions are available, we study the performance of the preliminary test generalized Liu estimators (PTGLEs) based on the Wald, likelihood ratio and Lagrangian multiplier tests. In this respect, the optimal range of the biasing parameter is obtained under the mean square error sense. For this, the minimum/maximum value of the biasing matrix components is used to give the proper optimal range, where the biasing matrix is D = diag(d1, d2, . . . , dp), 0 < di < 1, i = 1, . . . , p. We support our findings by some numerical illustrations.

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来源期刊

JIRSS-Journal of the Iranian Statistical Society STATISTICS & PROBABILITY-

CiteScore

1.50

自引率

0.00%

发文量