Threshold regression for modeling symbolic interval data
© Serials Publications Pvt.Ltd. This paper proposes a threshold regression model for symbolic interval data to explain the structural change in interval time series data. In this study, the center method and center-range method are applied in the thresold regression model and the parameters are esti...
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th-cmuir.6653943832-568882018-09-05T03:37:05Z Threshold regression for modeling symbolic interval data Panisara Phochanachan Pathairat Pastpipatkul Woraphon Yamaka Songsak Sriboonchitta Business, Management and Accounting Economics, Econometrics and Finance © Serials Publications Pvt.Ltd. This paper proposes a threshold regression model for symbolic interval data to explain the structural change in interval time series data. In this study, the center method and center-range method are applied in the thresold regression model and the parameters are estimated by Bayesian approach. The study employs Gibb sampler and Metropolis-Hastings alogorisms for drawing the parameter values. The results of simulation study and applications to real data are used to evaluate and show the usefullness of our proposed model. 2018-09-05T03:31:31Z 2018-09-05T03:31:31Z 2017-01-01 Journal 09727302 2-s2.0-85019584625 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85019584625&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/56888 |
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Business, Management and Accounting Economics, Econometrics and Finance Panisara Phochanachan Pathairat Pastpipatkul Woraphon Yamaka Songsak Sriboonchitta Threshold regression for modeling symbolic interval data |
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© Serials Publications Pvt.Ltd. This paper proposes a threshold regression model for symbolic interval data to explain the structural change in interval time series data. In this study, the center method and center-range method are applied in the thresold regression model and the parameters are estimated by Bayesian approach. The study employs Gibb sampler and Metropolis-Hastings alogorisms for drawing the parameter values. The results of simulation study and applications to real data are used to evaluate and show the usefullness of our proposed model. |
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Panisara Phochanachan Pathairat Pastpipatkul Woraphon Yamaka Songsak Sriboonchitta |
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Panisara Phochanachan Pathairat Pastpipatkul Woraphon Yamaka Songsak Sriboonchitta |
author_sort |
Panisara Phochanachan |
title |
Threshold regression for modeling symbolic interval data |
title_short |
Threshold regression for modeling symbolic interval data |
title_full |
Threshold regression for modeling symbolic interval data |
title_fullStr |
Threshold regression for modeling symbolic interval data |
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Threshold regression for modeling symbolic interval data |
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threshold regression for modeling symbolic interval data |
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2018 |
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https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85019584625&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/56888 |
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