Statistical significance of rank regression

Rank regression, which is quite simple to use some form of monotonic relationship between X and Y. Since the rank regression is a nonparametric approach so there are essentially no confidence interval, hypothesis tests, prediction intervals, and interpretation of regression coefficients. In this a...

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التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Rana, Sohel, Midi, Habshah, Fitrianto, Anwar
التنسيق: مقال
اللغة:English
English
منشور في: Hikari Ltd 2013
الوصول للمادة أونلاين:http://psasir.upm.edu.my/id/eprint/30316/1/Statistical%20significance%20of%20rank%20regression.pdf
http://psasir.upm.edu.my/id/eprint/30316/
http://www.m-hikari.com/ams/ams-2013/ams-81-84-2013/index.html
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spelling my.upm.eprints.303162015-10-30T03:23:24Z http://psasir.upm.edu.my/id/eprint/30316/ Statistical significance of rank regression Rana, Sohel Midi, Habshah Fitrianto, Anwar Rank regression, which is quite simple to use some form of monotonic relationship between X and Y. Since the rank regression is a nonparametric approach so there are essentially no confidence interval, hypothesis tests, prediction intervals, and interpretation of regression coefficients. In this article, we proposed a bootstrap statistical significance measure of the rank regression by formulating a bootstrap interval for the rank regression parameters. If the rank regression parameters from the original data are not within the bootstrap interval, the rank regression parameters are considered significance. Numerical examples show that the merit of using this proposed bootstrap interval. Hikari Ltd 2013 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/30316/1/Statistical%20significance%20of%20rank%20regression.pdf Rana, Sohel and Midi, Habshah and Fitrianto, Anwar (2013) Statistical significance of rank regression. Applied Mathematical Sciences, 7 (82). 4067-4072 . ISSN 1312-885X; ESSN: 1314-7552 http://www.m-hikari.com/ams/ams-2013/ams-81-84-2013/index.html English
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
English
description Rank regression, which is quite simple to use some form of monotonic relationship between X and Y. Since the rank regression is a nonparametric approach so there are essentially no confidence interval, hypothesis tests, prediction intervals, and interpretation of regression coefficients. In this article, we proposed a bootstrap statistical significance measure of the rank regression by formulating a bootstrap interval for the rank regression parameters. If the rank regression parameters from the original data are not within the bootstrap interval, the rank regression parameters are considered significance. Numerical examples show that the merit of using this proposed bootstrap interval.
format Article
author Rana, Sohel
Midi, Habshah
Fitrianto, Anwar
spellingShingle Rana, Sohel
Midi, Habshah
Fitrianto, Anwar
Statistical significance of rank regression
author_facet Rana, Sohel
Midi, Habshah
Fitrianto, Anwar
author_sort Rana, Sohel
title Statistical significance of rank regression
title_short Statistical significance of rank regression
title_full Statistical significance of rank regression
title_fullStr Statistical significance of rank regression
title_full_unstemmed Statistical significance of rank regression
title_sort statistical significance of rank regression
publisher Hikari Ltd
publishDate 2013
url http://psasir.upm.edu.my/id/eprint/30316/1/Statistical%20significance%20of%20rank%20regression.pdf
http://psasir.upm.edu.my/id/eprint/30316/
http://www.m-hikari.com/ams/ams-2013/ams-81-84-2013/index.html
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score 13.250246