How better are predictive models: Analysis on the practically important example of robust interval uncertainty

© Springer International Publishing AG 2018. One of the main applications of science and engineering is to predict future value of different quantities of interest. In the traditional statistical approach, we first use observations to estimate the parameters of an appropriate model, and then use the...

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Main Authors: Vladik Kreinovich, Hung T. Nguyen, Songsak Sriboonchitta, Olga Kosheleva
Format: Book Series
Published: 2018
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85037850732&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/43931
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-439312018-01-24T04:15:21Z How better are predictive models: Analysis on the practically important example of robust interval uncertainty Vladik Kreinovich Hung T. Nguyen Songsak Sriboonchitta Olga Kosheleva © Springer International Publishing AG 2018. One of the main applications of science and engineering is to predict future value of different quantities of interest. In the traditional statistical approach, we first use observations to estimate the parameters of an appropriate model, and then use the resulting estimates to make predictions. Recently, a relatively new predictive approach has been actively promoted, the approach where we make predictions directly from observations. It is known that in general, while the predictive approach requires more computations, it leads to more accurate predictions. In this paper, on the practically important example of robust interval uncertainty, we analyze how more accurate is the predictive approach. Our analysis shows that predictive models are indeed much more accurate: asymptotically, they lead to estimates which are √n more accurate, where n is the number of estimated parameters. 2018-01-24T04:15:21Z 2018-01-24T04:15:21Z 2018-01-01 Book Series 1860949X 2-s2.0-85037850732 10.1007/978-3-319-70942-0_13 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85037850732&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/43931
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
description © Springer International Publishing AG 2018. One of the main applications of science and engineering is to predict future value of different quantities of interest. In the traditional statistical approach, we first use observations to estimate the parameters of an appropriate model, and then use the resulting estimates to make predictions. Recently, a relatively new predictive approach has been actively promoted, the approach where we make predictions directly from observations. It is known that in general, while the predictive approach requires more computations, it leads to more accurate predictions. In this paper, on the practically important example of robust interval uncertainty, we analyze how more accurate is the predictive approach. Our analysis shows that predictive models are indeed much more accurate: asymptotically, they lead to estimates which are √n more accurate, where n is the number of estimated parameters.
format Book Series
author Vladik Kreinovich
Hung T. Nguyen
Songsak Sriboonchitta
Olga Kosheleva
spellingShingle Vladik Kreinovich
Hung T. Nguyen
Songsak Sriboonchitta
Olga Kosheleva
How better are predictive models: Analysis on the practically important example of robust interval uncertainty
author_facet Vladik Kreinovich
Hung T. Nguyen
Songsak Sriboonchitta
Olga Kosheleva
author_sort Vladik Kreinovich
title How better are predictive models: Analysis on the practically important example of robust interval uncertainty
title_short How better are predictive models: Analysis on the practically important example of robust interval uncertainty
title_full How better are predictive models: Analysis on the practically important example of robust interval uncertainty
title_fullStr How better are predictive models: Analysis on the practically important example of robust interval uncertainty
title_full_unstemmed How better are predictive models: Analysis on the practically important example of robust interval uncertainty
title_sort how better are predictive models: analysis on the practically important example of robust interval uncertainty
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85037850732&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/43931
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