The comparative forecast performance of univariate and multivariate model: an application to time series forecasting

Time series forecasting is a major challenge in many real world applications such as stock price analysis, electricity prices, natural rubber prices and flood forecasting. This type of forecasting is to predict the values of a continuous variable (called as response variable or output variable) with...

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Main Authors:	Sallehuddin, Roselina, Shamsuddin, Siti Mariyam, Mohd. Hashim, Siti Zaiton
Format:	Thesis
Published:	2009
Subjects:	QA75 Electronic computers Computer science
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id	my-utm-ep.18380
record_format	uketd_dc
spelling	my-utm-ep.183802012-08-07T02:05:52Z The comparative forecast performance of univariate and multivariate model: an application to time series forecasting 2009 Sallehuddin, Roselina Shamsuddin, Siti Mariyam Mohd. Hashim, Siti Zaiton QA75 Electronic computers. Computer science Time series forecasting is a major challenge in many real world applications such as stock price analysis, electricity prices, natural rubber prices and flood forecasting. This type of forecasting is to predict the values of a continuous variable (called as response variable or output variable) with a forecasting model based on historical data. There are two types of time series forecasting modeling methods; univariate and multivariate. 2009 Thesis http://eprints.utm.my/id/eprint/18380/ masters Universiti Teknologi Malaysia, Faculty of Computer Science and Information System Faculty of Computer Science and Information System
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
topic	QA75 Electronic computers Computer science
spellingShingle	QA75 Electronic computers Computer science Sallehuddin, Roselina Shamsuddin, Siti Mariyam Mohd. Hashim, Siti Zaiton The comparative forecast performance of univariate and multivariate model: an application to time series forecasting
description	Time series forecasting is a major challenge in many real world applications such as stock price analysis, electricity prices, natural rubber prices and flood forecasting. This type of forecasting is to predict the values of a continuous variable (called as response variable or output variable) with a forecasting model based on historical data. There are two types of time series forecasting modeling methods; univariate and multivariate.
format	Thesis
qualification_level	Master's degree
author	Sallehuddin, Roselina Shamsuddin, Siti Mariyam Mohd. Hashim, Siti Zaiton
author_facet	Sallehuddin, Roselina Shamsuddin, Siti Mariyam Mohd. Hashim, Siti Zaiton
author_sort	Sallehuddin, Roselina
title	The comparative forecast performance of univariate and multivariate model: an application to time series forecasting
title_short	The comparative forecast performance of univariate and multivariate model: an application to time series forecasting
title_full	The comparative forecast performance of univariate and multivariate model: an application to time series forecasting
title_fullStr	The comparative forecast performance of univariate and multivariate model: an application to time series forecasting
title_full_unstemmed	The comparative forecast performance of univariate and multivariate model: an application to time series forecasting
title_sort	comparative forecast performance of univariate and multivariate model: an application to time series forecasting
granting_institution	Universiti Teknologi Malaysia, Faculty of Computer Science and Information System
granting_department	Faculty of Computer Science and Information System
publishDate	2009
_version_	1747815260780232704

The comparative forecast performance of univariate and multivariate model: an application to time series forecasting

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