Forecasting pelagic fish in Malaysia using ets state space approach

Modelling and forecasting fish catch has been undertaken for a long time over the world. However, From time to time, researchers are always looking for a new model that can predict more accurately the number of fish catch. The objective of this study is to propose the Error Trend and Seasonal...

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Main Author:	Bako, Hadiza Yakubu
Format:	Thesis
Language:	English English English
Published:	2014
Subjects:	QA273-280 Probabilities Mathematical statistics
Online Access:	http://eprints.uthm.edu.my/1471/1/24p%20HADIZA%20YAKUBU%20BAKO.pdf http://eprints.uthm.edu.my/1471/2/HADIZA%20YAKUBU%20BAKO%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/1471/3/HADIZA%20YAKUBU%20BAKO%20WATERMARK.pdf
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spelling	my-uthm-ep.14712021-10-03T07:27:57Z Forecasting pelagic fish in Malaysia using ets state space approach 2014-12 Bako, Hadiza Yakubu QA273-280 Probabilities. Mathematical statistics Modelling and forecasting fish catch has been undertaken for a long time over the world. However, From time to time, researchers are always looking for a new model that can predict more accurately the number of fish catch. The objective of this study is to propose the Error Trend and Seasonal (ETS) state space approach.In this study, two techniques of time series analysis were used to forecast fish catch of three commercial fish species found in the Malaysian waters. One of such techniques is the Box-Jenkins method which concerns the building of linear and stochastic dynamic models with minimum data requirements. The second technique is the Error Trend and Seasonal (ETS) state space exponential method which requires no assumptions about the correlations between successive values of the time series. The two class models were used to model and forecast two years monthly catches of the three fish species based on the collected data for the period 2007 – 2011. The SARIMA(1,1,1)(0,0,1)[12], SARIMA(1,1,4)(0,0,1)[12], SARIMA(2,1,1)(0,0,1)[12] and ETS (M, A, M), ETS (M, N, M), ETS (M, A, M) for Dussumiera acuta (tamban buloh), Rastrelliger kanagurta (kembong) and Thunnus tonggol (Tongkol hitam) were proposed respectively. The diagnostic checking for all the fitted models confirmed the adequacy of the models. Results based on the root mean square error (RMSE) and mean absolute error (MAE) demonstrated that the ETS models per�formed better for Thunnus tonggol and Rastrelliger kanagurta, while SARIMA model performed better for Dussumiera acuta. This shows that ETS model which has so far not been used in fisheries in Malaysia is our main contribution in this research. Nevertheless, both models have proven successful in describing and forecasting the monthly fishery dynamics. These forecasts proves helpful in formulating the needed strategies for sustainable management and conservation of the stocks, and can also help the decision makers to establish priorities in terms of fisheries management. 2014-12 Thesis http://eprints.uthm.edu.my/1471/ http://eprints.uthm.edu.my/1471/1/24p%20HADIZA%20YAKUBU%20BAKO.pdf text en public http://eprints.uthm.edu.my/1471/2/HADIZA%20YAKUBU%20BAKO%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/1471/3/HADIZA%20YAKUBU%20BAKO%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Onn Malaysia Fakulti Sains Gunaan dan Teknologi
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	QA273-280 Probabilities Mathematical statistics
spellingShingle	QA273-280 Probabilities Mathematical statistics Bako, Hadiza Yakubu Forecasting pelagic fish in Malaysia using ets state space approach
description	Modelling and forecasting fish catch has been undertaken for a long time over the world. However, From time to time, researchers are always looking for a new model that can predict more accurately the number of fish catch. The objective of this study is to propose the Error Trend and Seasonal (ETS) state space approach.In this study, two techniques of time series analysis were used to forecast fish catch of three commercial fish species found in the Malaysian waters. One of such techniques is the Box-Jenkins method which concerns the building of linear and stochastic dynamic models with minimum data requirements. The second technique is the Error Trend and Seasonal (ETS) state space exponential method which requires no assumptions about the correlations between successive values of the time series. The two class models were used to model and forecast two years monthly catches of the three fish species based on the collected data for the period 2007 – 2011. The SARIMA(1,1,1)(0,0,1)[12], SARIMA(1,1,4)(0,0,1)[12], SARIMA(2,1,1)(0,0,1)[12] and ETS (M, A, M), ETS (M, N, M), ETS (M, A, M) for Dussumiera acuta (tamban buloh), Rastrelliger kanagurta (kembong) and Thunnus tonggol (Tongkol hitam) were proposed respectively. The diagnostic checking for all the fitted models confirmed the adequacy of the models. Results based on the root mean square error (RMSE) and mean absolute error (MAE) demonstrated that the ETS models per�formed better for Thunnus tonggol and Rastrelliger kanagurta, while SARIMA model performed better for Dussumiera acuta. This shows that ETS model which has so far not been used in fisheries in Malaysia is our main contribution in this research. Nevertheless, both models have proven successful in describing and forecasting the monthly fishery dynamics. These forecasts proves helpful in formulating the needed strategies for sustainable management and conservation of the stocks, and can also help the decision makers to establish priorities in terms of fisheries management.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Bako, Hadiza Yakubu
author_facet	Bako, Hadiza Yakubu
author_sort	Bako, Hadiza Yakubu
title	Forecasting pelagic fish in Malaysia using ets state space approach
title_short	Forecasting pelagic fish in Malaysia using ets state space approach
title_full	Forecasting pelagic fish in Malaysia using ets state space approach
title_fullStr	Forecasting pelagic fish in Malaysia using ets state space approach
title_full_unstemmed	Forecasting pelagic fish in Malaysia using ets state space approach
title_sort	forecasting pelagic fish in malaysia using ets state space approach
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Fakulti Sains Gunaan dan Teknologi
publishDate	2014
url	http://eprints.uthm.edu.my/1471/1/24p%20HADIZA%20YAKUBU%20BAKO.pdf http://eprints.uthm.edu.my/1471/2/HADIZA%20YAKUBU%20BAKO%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/1471/3/HADIZA%20YAKUBU%20BAKO%20WATERMARK.pdf
_version_	1747830797626245120

Forecasting pelagic fish in Malaysia using ets state space approach

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