关于“不规则直角三角形分布的参数估计量”的注记

Q4 Mathematics

Model Assisted Statistics and Applications Pub Date : 2021-12-20 DOI:10.3233/mas-210541

B. Lamond, Luckny Zéphyr

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引用次数: 1

摘要

在（Kachiashvili&Topchishvili，2016）中给出了不规则直角三角形分布的下限和上限的简单估计量，以及消除其偏差的方便公式。我们在这里认为，最小观测值不是下限的最大似然估计量（MLE），并且我们提出了计算该参数的MLE的过程。我们证明了MLE严格小于最小观测值，并给出了一些在数值求解过程中有用的边界。我们还提供了模拟结果来评估MLE的偏差和方差。

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Note on “Parameters estimators of irregular right-angled triangular distribution”

Simple estimators were given in (Kachiashvili & Topchishvili, 2016) for the lower and upper limits of an irregular right-angled triangular distribution together with convenient formulas for removing their bias. We argue here that the smallest observation is not a maximum likelihood estimator (MLE) of the lower limit and we present a procedure for computing an MLE of this parameter. We show that the MLE is strictly smaller than the smallest observation and we give some bounds that are useful in a numerical solution procedure. We also present simulation results to assess the bias and variance of the MLE.

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来源期刊

Model Assisted Statistics and Applications Mathematics-Applied Mathematics

CiteScore

1.00

自引率

0.00%

发文量

期刊介绍： Model Assisted Statistics and Applications is a peer reviewed international journal. Model Assisted Statistics means an improvement of inference and analysis by use of correlated information, or an underlying theoretical or design model. This might be the design, adjustment, estimation, or analytical phase of statistical project. This information may be survey generated or coming from an independent source. Original papers in the field of sampling theory, econometrics, time-series, design of experiments, and multivariate analysis will be preferred. Papers of both applied and theoretical topics are acceptable.