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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English English |
| Published: |
Hikari Ltd
2013
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| Online Access: | http://psasir.upm.edu.my/id/eprint/30316/1/Statistical%20significance%20of%20rank%20regression.pdf |
| _version_ | 1825947683064381440 |
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| author | Rana, Sohel Midi, Habshah Fitrianto, Anwar |
| author_facet | Rana, Sohel Midi, Habshah Fitrianto, Anwar |
| author_sort | Rana, Sohel |
| collection | UPM |
| 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. |
| first_indexed | 2024-03-06T08:17:12Z |
| format | Article |
| id | upm.eprints-30316 |
| institution | Universiti Putra Malaysia |
| language | English English |
| last_indexed | 2024-03-06T08:17:12Z |
| publishDate | 2013 |
| publisher | Hikari Ltd |
| record_format | dspace |
| spelling | 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 |
| spellingShingle | Rana, Sohel Midi, Habshah Fitrianto, Anwar Statistical significance of rank regression |
| title | 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_short | Statistical significance of rank regression |
| title_sort | statistical significance of rank regression |
| url | http://psasir.upm.edu.my/id/eprint/30316/1/Statistical%20significance%20of%20rank%20regression.pdf |
| work_keys_str_mv | AT ranasohel statisticalsignificanceofrankregression AT midihabshah statisticalsignificanceofrankregression AT fitriantoanwar statisticalsignificanceofrankregression |