Construction of Bivariate Copulas on the Hotelling's T2 Control Chart

被引：0

作者：

Tiengket, Sanpet ^{[1
]}

Sukparungsee, Saowanit ^{[1
]}

Busababodhin, Piyapatr ^{[2
]}

Areepong, Yupaporn ^{[1
]}

机构：

[1] King Mongkuts Univ Technol North Bangkok, Fac Appl Sci, Dept Appl Stat, Bangkok, Thailand

[2] Mahasarakham Univ, Fac Sci, Dept Math, Kantarawichai, Mahasarakham, Thailand

来源：

THAILAND STATISTICIAN | 2020年 / 18卷 / 01期

关键词：

Marginal distribution; joint distribution; multivariate control chart; Monte Carlo simulation; STATISTICAL PROCESS-CONTROL; DISTRIBUTIONS;

D O I：

暂无

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：

In this paper, five types of copulas, which are Gumbel, Clayton, Farlie-Gumbel-Morgenstern (FGM), Frank and Ali-Mikail-Haq (AMH) copulas are presented via construction of bivariate copulas on the Hotelling's T-2 control chart. The observations are generated from the exponential distribution and the dependent observations are measured by Kendall's tau (tau) values as weak, moderate and strongly positive dependences where tau are 0.1, 0.2, 0.5, 0.6, 0.8 and 0.9, respectively. Monte Carlo simulation was used to compare the performance of the control chart with the Average Run Length (ARL) as performance metric. The results indicate that the bivariate copulas approach can be fitted to the Hotelling's T-2 control chart.

引用

页码：1 / 15

页数：15

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