A General Class of Tests for Testing Homogeneity of Location Parameters against Umbrella Alternatives

In this paper, a general class of non-parametric tests for testing homogeneity of location parameter against umbrella alternatives is proposed. Testing for umbrella alternatives has many applications in the field of biology, medicine, botany, dose level testing, engineering, economics, psychology, z...

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Main Authors: Manish Goyal, Narinder Kumar
Format: Article
Language:English
Published: International Journal of Mathematical, Engineering and Management Sciences 2018-12-01
Series:International Journal of Mathematical, Engineering and Management Sciences
Subjects:
Online Access:https://www.ijmems.in/assets//36-ijmems-18-012-vol.-3%2c-no.-4%2c-498%E2%80%93512%2c-2018.pdf
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spelling doaj-a1d35d4fbd8d495484cd601e73afe9022020-11-25T01:18:48ZengInternational Journal of Mathematical, Engineering and Management SciencesInternational Journal of Mathematical, Engineering and Management Sciences2455-77492455-77492018-12-013449851210.33889/IJMEMS.2018.3.4-036A General Class of Tests for Testing Homogeneity of Location Parameters against Umbrella AlternativesManish Goyal0Narinder Kumar1Department of Statistics, Panjab University, Chandigarh, IndiaDepartment of Statistics, Panjab University, Chandigarh, IndiaIn this paper, a general class of non-parametric tests for testing homogeneity of location parameter against umbrella alternatives is proposed. Testing for umbrella alternatives has many applications in the field of biology, medicine, botany, dose level testing, engineering, economics, psychology, zoology. As an example, the effectiveness of a drug is likely to increase with increase of dose up to a certain level and then its effect begins to decrease. The proposed test is based on linear combination of two-sample U-statistics. The null distribution of the test statistics is developed. We compare the test with some other competing tests in terms of Pitman asymptotic relative efficiency. To see execution of the test, a numerical example is provided. Simulation study is carried out to assess the power of proposed class of tests.https://www.ijmems.in/assets//36-ijmems-18-012-vol.-3%2c-no.-4%2c-498%E2%80%93512%2c-2018.pdfNon-parametric testsUmbrella alternativesNull distributionPitman efficiencySimulation study
collection DOAJ
language English
format Article
sources DOAJ
author Manish Goyal
Narinder Kumar
spellingShingle Manish Goyal
Narinder Kumar
A General Class of Tests for Testing Homogeneity of Location Parameters against Umbrella Alternatives
International Journal of Mathematical, Engineering and Management Sciences
Non-parametric tests
Umbrella alternatives
Null distribution
Pitman efficiency
Simulation study
author_facet Manish Goyal
Narinder Kumar
author_sort Manish Goyal
title A General Class of Tests for Testing Homogeneity of Location Parameters against Umbrella Alternatives
title_short A General Class of Tests for Testing Homogeneity of Location Parameters against Umbrella Alternatives
title_full A General Class of Tests for Testing Homogeneity of Location Parameters against Umbrella Alternatives
title_fullStr A General Class of Tests for Testing Homogeneity of Location Parameters against Umbrella Alternatives
title_full_unstemmed A General Class of Tests for Testing Homogeneity of Location Parameters against Umbrella Alternatives
title_sort general class of tests for testing homogeneity of location parameters against umbrella alternatives
publisher International Journal of Mathematical, Engineering and Management Sciences
series International Journal of Mathematical, Engineering and Management Sciences
issn 2455-7749
2455-7749
publishDate 2018-12-01
description In this paper, a general class of non-parametric tests for testing homogeneity of location parameter against umbrella alternatives is proposed. Testing for umbrella alternatives has many applications in the field of biology, medicine, botany, dose level testing, engineering, economics, psychology, zoology. As an example, the effectiveness of a drug is likely to increase with increase of dose up to a certain level and then its effect begins to decrease. The proposed test is based on linear combination of two-sample U-statistics. The null distribution of the test statistics is developed. We compare the test with some other competing tests in terms of Pitman asymptotic relative efficiency. To see execution of the test, a numerical example is provided. Simulation study is carried out to assess the power of proposed class of tests.
topic Non-parametric tests
Umbrella alternatives
Null distribution
Pitman efficiency
Simulation study
url https://www.ijmems.in/assets//36-ijmems-18-012-vol.-3%2c-no.-4%2c-498%E2%80%93512%2c-2018.pdf
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