Why is linear quantile regression empirically successful: A possible explanation

© Springer International Publishing AG 2017. Many quantities describing the physical world are related to each other. As a result, often, when we know the values of certain quantities x 1 ,…, x n , we can reasonably well predict the value of some other quantity y. In many application, in addition to...

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Main Authors: Hung T. Nguyen, Vladik Kreinovich, Olga Kosheleva, Songsak Sriboonchitta
Format: Book Series
Published: 2018
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Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85012066355&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/46739
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-467392018-04-25T07:32:32Z Why is linear quantile regression empirically successful: A possible explanation Hung T. Nguyen Vladik Kreinovich Olga Kosheleva Songsak Sriboonchitta Agricultural and Biological Sciences © Springer International Publishing AG 2017. Many quantities describing the physical world are related to each other. As a result, often, when we know the values of certain quantities x 1 ,…, x n , we can reasonably well predict the value of some other quantity y. In many application, in addition to the resulting estimate for y, it is also desirable to predict how accurate is this approximate estimate, i.e., what is the probability distribution of different possible values y. It turns out that in many cases, the quantiles of this distribution linearly depend on the values x 1 ,…, x n . In this paper, we provide a possible theoretical explanation for this somewhat surprising empirical success of such linear quantile regression. 2018-04-25T07:00:05Z 2018-04-25T07:00:05Z 2017-01-01 Book Series 1860949X 2-s2.0-85012066355 10.1007/978-3-319-51052-1_11 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85012066355&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/46739
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Agricultural and Biological Sciences
spellingShingle Agricultural and Biological Sciences
Hung T. Nguyen
Vladik Kreinovich
Olga Kosheleva
Songsak Sriboonchitta
Why is linear quantile regression empirically successful: A possible explanation
description © Springer International Publishing AG 2017. Many quantities describing the physical world are related to each other. As a result, often, when we know the values of certain quantities x 1 ,…, x n , we can reasonably well predict the value of some other quantity y. In many application, in addition to the resulting estimate for y, it is also desirable to predict how accurate is this approximate estimate, i.e., what is the probability distribution of different possible values y. It turns out that in many cases, the quantiles of this distribution linearly depend on the values x 1 ,…, x n . In this paper, we provide a possible theoretical explanation for this somewhat surprising empirical success of such linear quantile regression.
format Book Series
author Hung T. Nguyen
Vladik Kreinovich
Olga Kosheleva
Songsak Sriboonchitta
author_facet Hung T. Nguyen
Vladik Kreinovich
Olga Kosheleva
Songsak Sriboonchitta
author_sort Hung T. Nguyen
title Why is linear quantile regression empirically successful: A possible explanation
title_short Why is linear quantile regression empirically successful: A possible explanation
title_full Why is linear quantile regression empirically successful: A possible explanation
title_fullStr Why is linear quantile regression empirically successful: A possible explanation
title_full_unstemmed Why is linear quantile regression empirically successful: A possible explanation
title_sort why is linear quantile regression empirically successful: a possible explanation
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85012066355&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/46739
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