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ESTIMATING THE VARIANCE OF A NORMAL POPULATION BY UTILIZING THE INFORMATION IN A SAMPLE FROM A SECOND RELATED NORMAL POPULATION

机译:利用来自第二个相关正常人口的样本中的信息来估计正常人口的变化

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摘要

A class of estimators of the variance σ_1~2 of a normal population is introduced, by utilization the information in a sample from a second normal population with different mean and variance σ_2~2, under the restriction that σ_1~2 ≤ σ_2~2. Simulation results indicate that some members of this class are more efficient than the usual minimum variance unbiased estimator (MVUE) of σ_1~2, Stein estimator and Mehta and Gurland estimator. The case of known and unknown means are considered.
机译:在σ_1〜2≤σ_2〜2的限制下,通过利用均值和方差为σ_2〜2的第二个正常群体的样本中的信息,引入一类正常人群的方差σ_1〜2的估计量。仿真结果表明,该类中的某些成员比通常的σ_1〜2最小最小方差无偏估计器(MVUE),Stein估计器以及Mehta和Gurland估计器更有效。考虑已知和未知方法的情况。

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