Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/55978
Title: Time series forecast using AR-belief approach
Authors: Nantiworn Thianpaen
Jianxu Liu
Songsak Sriboonchitta
Authors: Nantiworn Thianpaen
Jianxu Liu
Songsak Sriboonchitta
Keywords: Mathematics
Issue Date: 1-Jan-2016
Abstract: © 2016 by the Mathematical Association of Thailand. All rights reserved. This paper aims at applying a recent new approach to predicting the growth rate of Thailand GDP. The new approach will provide uncertainty about predicted values solely from observed data without the need to supply some subjective prior distribution on unknown model parameters. This is achieved by building a belief function (i.e., a distribution of a random set) from the likelihood function given the observed data, and use it to assess prediction uncertainty. With our sampling model as an autoregressive time series model, we demonstrate em-pirically that this approach can provide a reliable con_dence interval for predicted values.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85008185815&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/55978
ISSN: 16860209
Appears in Collections:CMUL: Journal Articles

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