倾斜对数拉普拉斯分布的倾斜参数测试

Q4 Mathematics

Model Assisted Statistics and Applications Pub Date : 2023-12-27 DOI:10.3233/mas-221423

Pradnya P. Khandeparkar, Vaijayanti Dixit

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引用次数: 0

摘要

拉普拉斯概率密度函数带有调节偏斜程度的附加形状参数，这就是偏斜拉普拉斯分布。偏斜拉普拉斯分布的形式多种多样，文献中有 Mc Gill (1962)、Holla 和 Bhattacharya (1968)、Lingappaiah (1988)、Fernandez 和 Steel (1998) 所定义的分布。偏斜对数拉普拉斯分布是指对数服从偏斜拉普拉斯分布的随机变量的概率分布。本文讨论了由 Lingappaiah（1988）分布导出的偏斜对拉普拉斯分布（SLLD）偏斜参数的经典最优检验。比较了斜度参数的均匀最强检验、均匀最强无偏检验和 Wald 连续似然比检验。得出了在尺度参数已知的情况下检验偏度参数的精确似然比检验和奈曼结构检验。最后，根据本文得出的检验方法对道路运输公司的少报收入进行了分析。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Tests for skewness parameter of skew log Laplace distribution

Laplace probability density function with additional shape parameter that regulates the degree of skewness is a skew Laplace distribution. The various forms of skew Laplace distribution are found in the literature, the distributions defined by Mc Gill (1962), Holla and Bhattacharya (1968), Lingappaiah (1988), Fernandez and Steel (1998). The skew log Laplace distribution is the probability distribution of a random variable whose logarithm follows a skew Laplace distribution. In this paper, the classical optimum tests for skewness parameter of skew log Laplace distribution (SLLD) derived from Lingappaiah (1988) distribution are discussed. Uniformly most powerful test, uniformly most powerful unbiased test and Wald’s sequential probability ratio test for skewness parameter are compared. The exact likelihood ratio test and Neyman structure test for testing skewness parameter when scale parameter is known are derived. Finally, the underreported income of Road Transport Company is analysed on the basis of the tests derived in this paper.

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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.