Multiple regression model for forecasting quantity of supply of off-season longan

This research work aims to develop a forecasting model to predict the quantity of supply of off-season longan using multiple regression technique. There are 23 factors that influence the quantity of supply of off-season longan. Data collection was done in Chiang Mai and Lamphun provinces. The foreca...

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Main Authors:	Chompoonoot Kasemset, Nisachon Sae-Haew, Apichat Sopadang
Format:	Journal
Published:	2018
Online Access:	https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84963955004&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/45274
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Institution:	Chiang Mai University

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spelling	th-cmuir.6653943832-452742018-01-24T06:07:42Z Multiple regression model for forecasting quantity of supply of off-season longan Chompoonoot Kasemset Nisachon Sae-Haew Apichat Sopadang This research work aims to develop a forecasting model to predict the quantity of supply of off-season longan using multiple regression technique. There are 23 factors that influence the quantity of supply of off-season longan. Data collection was done in Chiang Mai and Lamphun provinces. The forecasting model based on multiple regression techniques, with enter, forward, backward, and stepwise selection methods were adopted, and these methods yielded mean absolute percentage error (MAPE) values of 18.39%, 25.63%, 21.21%, and 25.63%, respectively. These results demonstrate that multiple regression with the enter selection method is practical to predict the quantity of supply of off-season longan. 2018-01-24T06:07:42Z 2018-01-24T06:07:42Z 2014-01-01 Journal 16851994 2-s2.0-84963955004 10.12982/cmujns.2014.0044 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84963955004&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/45274
institution	Chiang Mai University
building	Chiang Mai University Library
country	Thailand
collection	CMU Intellectual Repository
description	This research work aims to develop a forecasting model to predict the quantity of supply of off-season longan using multiple regression technique. There are 23 factors that influence the quantity of supply of off-season longan. Data collection was done in Chiang Mai and Lamphun provinces. The forecasting model based on multiple regression techniques, with enter, forward, backward, and stepwise selection methods were adopted, and these methods yielded mean absolute percentage error (MAPE) values of 18.39%, 25.63%, 21.21%, and 25.63%, respectively. These results demonstrate that multiple regression with the enter selection method is practical to predict the quantity of supply of off-season longan.
format	Journal
author	Chompoonoot Kasemset Nisachon Sae-Haew Apichat Sopadang
spellingShingle	Chompoonoot Kasemset Nisachon Sae-Haew Apichat Sopadang Multiple regression model for forecasting quantity of supply of off-season longan
author_facet	Chompoonoot Kasemset Nisachon Sae-Haew Apichat Sopadang
author_sort	Chompoonoot Kasemset
title	Multiple regression model for forecasting quantity of supply of off-season longan
title_short	Multiple regression model for forecasting quantity of supply of off-season longan
title_full	Multiple regression model for forecasting quantity of supply of off-season longan
title_fullStr	Multiple regression model for forecasting quantity of supply of off-season longan
title_full_unstemmed	Multiple regression model for forecasting quantity of supply of off-season longan
title_sort	multiple regression model for forecasting quantity of supply of off-season longan
publishDate	2018
url	https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84963955004&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/45274
_version_	1681422714730971136

Multiple regression model for forecasting quantity of supply of off-season longan

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