Testing of mean interval for interval-valued data

被引：2

作者：

Roy, Anuradha ^{[1
]}

Klein, Daniel ^{[2
]}

机构：

[1] Univ Texas San Antonio, Dept Management Sci & Stat, One UTSA Circle, San Antonio, TX 78249 USA

[2] Safarik Univ, Fac Sci, Inst Math, Kosice, Slovakia

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2020年 / 49卷 / 20期

关键词：

Interval data; Hypothesis testing; Orthogonal transformation; REGRESSION;

D O I：

10.1080/03610926.2019.1612915

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：

A new parametric hypothesis test of mean interval for interval-valued data set, which can deal with massive information contained in nowadays massive data "Big data" sets, is proposed. An approach using an orthogonal transformation is introduced to obtain an equivalent hypothesis test of mean interval in terms of the mid-point and mid-range of the interval-valued variable. The new test is very efficient in small interval-valued sample scenarios. Some simulation studies are conducted for the investigation of the sample size and the power of test. The performance of the proposed test is illustrated with two real-life examples.

引用

页码：5028 / 5044

页数：17

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