Testing the difference between two sets of data using comparison two linear regression functions

被引：0

作者：

Tonggumnead, Unchalee ^{[1
]}

机构：

[1] Rajamangala Univ Technol Thanyaburi RMUTT, Fac Sci & Technol, Dept Math & Comp Sci, Div Appl Stat, 39 Moo 1,Rangsit Nakhonnayok Rd,Klong 6, Thanyaburi 12110, Pathumthani, Thailand

来源：

ELECTRONIC JOURNAL OF APPLIED STATISTICAL ANALYSIS | 2014年 / 7卷 / 02期

关键词：

regression function; linear relationship; empirical distribution function; bootstrap procedure; error distribution;

D O I：

10.1285/i20705948v7n2p279

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：

This study aims to compare two sets of data with each having a linear relationship between the independent and dependent variables. The problem is solved by testing the equality of two regression functions. The test statistics based on empirical distribution function: the Kolmogorov-Smirnov and Kuiper type statistics are considered, under the alternative hypotheses comprised of a constant shift and an affine shift. Additionally, the rejection proportion is calculated using the bootstrap method. The test statistics are also applied to the analysis of two sets of data, the characteristics of which are found to be consistent with the p-value after 1,000 trials of bootstrapping..

引用

页码：279 / 291

页数：13

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