The generalize maximum Tsallis entropy estimator in kink regression model

The generalize maximum Tsallis entropy estimator in kink regression model

© Published under licence by IOP Publishing Ltd. Under the limited information situation, underdetermined or ill-posed problem in statistical inference is likely to arise. To solve these problems the generalized maximum entropy (GME) was proposed. In this study, we apply a generalized maximum Tsalli...

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Main Authors: Payap Tarkhamtham, Woraphon Yamaka, Songsak Sriboonchitta
Format: Conference Proceeding
Published: 2018
Subjects:
Physics and Astronomy
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85051392698&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/59130
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-591302018-09-05T04:38:51Z The generalize maximum Tsallis entropy estimator in kink regression model Payap Tarkhamtham Woraphon Yamaka Songsak Sriboonchitta Physics and Astronomy © Published under licence by IOP Publishing Ltd. Under the limited information situation, underdetermined or ill-posed problem in statistical inference is likely to arise. To solve these problems the generalized maximum entropy (GME) was proposed. In this study, we apply a generalized maximum Tsallis entropy (Tsallis GME) to estimate the kink regression using Monte Carlo Simulation and find that Tsallis GME performs better than the Least squares and Maximum likelihood estimators when the error is generated from unknown distribution. In addition, we can claim that the GME is a robust estimator and suggest that Tsallis GME can be used as an alternative estimator for kink regression model. 2018-09-05T04:38:51Z 2018-09-05T04:38:51Z 2018-07-26 Conference Proceeding 17426596 17426588 2-s2.0-85051392698 10.1088/1742-6596/1053/1/012103 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85051392698&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/59130
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Physics and Astronomy
spellingShingle Physics and Astronomy
Payap Tarkhamtham
Woraphon Yamaka
Songsak Sriboonchitta
The generalize maximum Tsallis entropy estimator in kink regression model
description © Published under licence by IOP Publishing Ltd. Under the limited information situation, underdetermined or ill-posed problem in statistical inference is likely to arise. To solve these problems the generalized maximum entropy (GME) was proposed. In this study, we apply a generalized maximum Tsallis entropy (Tsallis GME) to estimate the kink regression using Monte Carlo Simulation and find that Tsallis GME performs better than the Least squares and Maximum likelihood estimators when the error is generated from unknown distribution. In addition, we can claim that the GME is a robust estimator and suggest that Tsallis GME can be used as an alternative estimator for kink regression model.
format Conference Proceeding
author Payap Tarkhamtham
Woraphon Yamaka
Songsak Sriboonchitta
author_facet Payap Tarkhamtham
Woraphon Yamaka
Songsak Sriboonchitta
author_sort Payap Tarkhamtham
title The generalize maximum Tsallis entropy estimator in kink regression model
title_short The generalize maximum Tsallis entropy estimator in kink regression model
title_full The generalize maximum Tsallis entropy estimator in kink regression model
title_fullStr The generalize maximum Tsallis entropy estimator in kink regression model
title_full_unstemmed The generalize maximum Tsallis entropy estimator in kink regression model
title_sort generalize maximum tsallis entropy estimator in kink regression model
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85051392698&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/59130
_version_ 1681425194318561280

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