On sensitivity of exponentiality tests to data rounding: a Monte Carlo simulation study

被引：2

作者：

Ushakov, N. G. ^{[1
]}

Ushakov, V. G. ^{[2
,3
]}

机构：

[1] Norwegian Univ Sci & Technol, Dept Math Sci, N-7491 Trondheim, Norway

[2] Lomonosov Moscow State Univ, Moscow, Russia

[3] Russian Acad Sci, Fed Res Ctr Comp Sci & Control, Moscow, Russia

来源：

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2023年 / 52卷 / 12期

关键词：

Exponential distribution; Monte Carlo simulation; rounded data; significance level; test for exponentiality; DENSITY;

D O I：

10.1080/03610918.2021.2009868

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Different statistical procedures are differently sensitive to data rounding. It turns out that tests for exponentiality are more sensitive to the data rounding than many classical parametric tests or than nonparametric tests for normality. In this work we find out which exponentiality tests are more robust and which ones are less robust to the rounding. The main tool is Monte Carlo simulation. We estimate and compare the probability of Type I error of nineteen exponentiality tests for different rounding levels and different sample sizes.

引用

页码：6225 / 6234

页数：10

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