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Inference for the Normal Mean with Known Coefficient of Variation

机译:具有已知变异系数的法线均值的推论

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Inference for the mean of a normal distribution with known coefficient of variation is of special theoretical interest be- cause the model belongs to the curved exponential family with a scalar parameter of interest and a two-dimensional minimal sufficient statistic. Therefore, standard inferential methods cannot be directly applied to this problem. It is also of practical interest because this problem arises naturally in many environmental and agriculture studies. In this paper we proposed a modified signed log likelihood ratio method to obtain inference for the normal mean with known coeffi- cient of variation. Simulation studies show the remarkable accuracy of the proposed method even for sample size as small as 2. Moreover, a new point estimator for the mean can be derived from the proposed method. Simulation studies show that new point estimator is more efficient than most of the existing estimators.
机译:具有已知变异系数的正态分布均值的推断具有特殊的理论意义,因为该模型属于具有标量参数和二维最小充分统计量的弯曲指数族。因此,标准推论方法不能直接应用于此问题。它也具有实际意义,因为在许多环境和农业研究中自然会出现此问题。在本文中,我们提出了一种改进的带符号对数似然比方法,以获得具有已知变异系数的法线均值的推论。仿真研究表明,即使样本量小至2,该方法也具有显着的准确性。此外,可以从该方法中得出新的均值点估计器。仿真研究表明,新的点估计器比大多数现有估计器更有效。

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