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On the Existence and Uniqueness of the Maximum Likelihood Estimators of Normal and Lognormal Population Parameters with Grouped Data

机译:具有分组数据的正态和对数正态总体参数的最大似然估计的存在性和唯一性

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Lognormal distribution has abundant applications in various fields. In literature,most inferences on the two parameters of the lognormal distribution arebased on Type-I censored sample data. However, exact measurements are not alwaysattainable especially when the observation is below or above the detectionlimits, and only the numbers of measurements falling into predetermined intervalscan be recorded instead. This is the so-called grouped data. In this paper, we willshow the existence and uniqueness of the maximum likelihood estimators of the twoparameters of the underlying lognormal distribution with Type-I censored data andgrouped data. The proof was first established under the case of normal distributionand extended to the lognormal distribution through invariance property. Theresults are applied to estimate the median and mean of the lognormal population.
机译:对数正态分布在各个领域都有广泛的应用。在文献中,关于对数正态分布的两个参数的大多数推论都是基于I型审查样本数据。但是,尤其是当观察值低于或超过检测极限时,始终无法获得精确的测量值,而是只能记录落入预定间隔的测量值数量。这就是所谓的分组数据。在本文中,我们将展示具有I型删失数据和分组数据的基本对数正态分布的两个参数的最大似然估计的存在性和唯一性。证明首先建立在正态分布的情况下,并通过不变性扩展到对数正态分布。结果用于估计对数正态总体的中位数和均值。

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