Comparison of Conjugate Gradient methods for developing the multiple linear regression model for rubber yield in Malaysia / Anis Shahida Rohimi Ozeman

Regression analysis is known as a statistical technique for estimating the relationship between variables which have reason and result relation. In this research, regression models with one dependent variable and more than one independent's variable called multiple linear regression (MLR) is be...

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Main Author:	Rohimi Ozeman, Anis Shahida
Format:	Thesis
Language:	English
Published:	2018
Subjects:	Mathematical statistics Probabilities Analysis Algorithms
Online Access:	https://ir.uitm.edu.my/id/eprint/39997/1/39997.pdf
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id	my-uitm-ir.39997
record_format	uketd_dc
spelling	my-uitm-ir.399972024-07-01T07:21:06Z Comparison of Conjugate Gradient methods for developing the multiple linear regression model for rubber yield in Malaysia / Anis Shahida Rohimi Ozeman 2018-07 Rohimi Ozeman, Anis Shahida Mathematical statistics. Probabilities Analysis Algorithms Regression analysis is known as a statistical technique for estimating the relationship between variables which have reason and result relation. In this research, regression models with one dependent variable and more than one independent's variable called multiple linear regression (MLR) is been used to produce a regression model for rubber yield in Malaysia. Meanwhile, Conjugate Gradient (CG) method is used to solve regression parameter through the normal equation since it is a well-known method due to the simplicity, easiness and low memory requirement. The selected CG formulas are from classical CG which is Fletcher-Reeves (FR), Polak-Ribiere-Polyak (PRP), Hestenes-Stiefel (HS), and Rivaie et al. (RMIL). Then, the result from MLR, selected variants of CG method and inverse matrix method will be compared. Based on the result, beta coefficient of CG-FR proved to be best method to produce the best regression model with the least root mean square error value. 2018-07 Thesis https://ir.uitm.edu.my/id/eprint/39997/ https://ir.uitm.edu.my/id/eprint/39997/1/39997.pdf text en public degree Universiti Teknologi MARA Faculty of Computer and Mathematical Sciences Norddin, Nur Idalisa
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Norddin, Nur Idalisa
topic	Mathematical statistics Probabilities Analysis Algorithms
spellingShingle	Mathematical statistics Probabilities Analysis Algorithms Rohimi Ozeman, Anis Shahida Comparison of Conjugate Gradient methods for developing the multiple linear regression model for rubber yield in Malaysia / Anis Shahida Rohimi Ozeman
description	Regression analysis is known as a statistical technique for estimating the relationship between variables which have reason and result relation. In this research, regression models with one dependent variable and more than one independent's variable called multiple linear regression (MLR) is been used to produce a regression model for rubber yield in Malaysia. Meanwhile, Conjugate Gradient (CG) method is used to solve regression parameter through the normal equation since it is a well-known method due to the simplicity, easiness and low memory requirement. The selected CG formulas are from classical CG which is Fletcher-Reeves (FR), Polak-Ribiere-Polyak (PRP), Hestenes-Stiefel (HS), and Rivaie et al. (RMIL). Then, the result from MLR, selected variants of CG method and inverse matrix method will be compared. Based on the result, beta coefficient of CG-FR proved to be best method to produce the best regression model with the least root mean square error value.
format	Thesis
qualification_level	Bachelor degree
author	Rohimi Ozeman, Anis Shahida
author_facet	Rohimi Ozeman, Anis Shahida
author_sort	Rohimi Ozeman, Anis Shahida
title	Comparison of Conjugate Gradient methods for developing the multiple linear regression model for rubber yield in Malaysia / Anis Shahida Rohimi Ozeman
title_short	Comparison of Conjugate Gradient methods for developing the multiple linear regression model for rubber yield in Malaysia / Anis Shahida Rohimi Ozeman
title_full	Comparison of Conjugate Gradient methods for developing the multiple linear regression model for rubber yield in Malaysia / Anis Shahida Rohimi Ozeman
title_fullStr	Comparison of Conjugate Gradient methods for developing the multiple linear regression model for rubber yield in Malaysia / Anis Shahida Rohimi Ozeman
title_full_unstemmed	Comparison of Conjugate Gradient methods for developing the multiple linear regression model for rubber yield in Malaysia / Anis Shahida Rohimi Ozeman
title_sort	comparison of conjugate gradient methods for developing the multiple linear regression model for rubber yield in malaysia / anis shahida rohimi ozeman
granting_institution	Universiti Teknologi MARA
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2018
url	https://ir.uitm.edu.my/id/eprint/39997/1/39997.pdf
_version_	1804889634013970432

Comparison of Conjugate Gradient methods for developing the multiple linear regression model for rubber yield in Malaysia / Anis Shahida Rohimi Ozeman

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