Comparison of conjugate gradient methods for developing the multiple linear regression model for rice production in Malaysia / Nur Atikah Mustapha

Linear regression is one of the basic model in statistics and it is also categorized an unconstrained optimization problem. It is used to determine the relationship between dependent and independent variables. This project focuses on the formation of regression models for the rice production in Mala...

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Main Author:	Mustapha, Nur Atikah
Format:	Thesis
Language:	English
Published:	2018
Subjects:	Mathematical statistics Probabilities Analysis Nonlinear theories Algorithms
Online Access:	https://ir.uitm.edu.my/id/eprint/41320/1/41320.pdf
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id	my-uitm-ir.41320
record_format	uketd_dc
spelling	my-uitm-ir.413202024-07-01T07:59:36Z Comparison of conjugate gradient methods for developing the multiple linear regression model for rice production in Malaysia / Nur Atikah Mustapha 2018 Mustapha, Nur Atikah Mathematical statistics. Probabilities Analysis Nonlinear theories Algorithms Linear regression is one of the basic model in statistics and it is also categorized an unconstrained optimization problem. It is used to determine the relationship between dependent and independent variables. This project focuses on the formation of regression models for the rice production in Malaysia by analyzing the effects of paddy population, planted area, human population and domestic consumption. The conjugate gradient method is used to solve the regression function through normal equation in matrix form. The conjugate gradient is chosen due to its ability to generate a solution for regression model and obtain the coefficient value of independent variables. The beta parameter from general conjugate equation is varied using four existing formula. The conjugate method is then compared with the result obtained from direct method and SPSS software. From the comparison, the conjugate gradient method with beta FR (Fletcher and Reeves) shows the least absolute error and declared as the best regression model for the rice production statistic. 2018 Thesis https://ir.uitm.edu.my/id/eprint/41320/ https://ir.uitm.edu.my/id/eprint/41320/1/41320.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 Nonlinear theories Algorithms
spellingShingle	Mathematical statistics Probabilities Analysis Nonlinear theories Algorithms Mustapha, Nur Atikah Comparison of conjugate gradient methods for developing the multiple linear regression model for rice production in Malaysia / Nur Atikah Mustapha
description	Linear regression is one of the basic model in statistics and it is also categorized an unconstrained optimization problem. It is used to determine the relationship between dependent and independent variables. This project focuses on the formation of regression models for the rice production in Malaysia by analyzing the effects of paddy population, planted area, human population and domestic consumption. The conjugate gradient method is used to solve the regression function through normal equation in matrix form. The conjugate gradient is chosen due to its ability to generate a solution for regression model and obtain the coefficient value of independent variables. The beta parameter from general conjugate equation is varied using four existing formula. The conjugate method is then compared with the result obtained from direct method and SPSS software. From the comparison, the conjugate gradient method with beta FR (Fletcher and Reeves) shows the least absolute error and declared as the best regression model for the rice production statistic.
format	Thesis
qualification_level	Bachelor degree
author	Mustapha, Nur Atikah
author_facet	Mustapha, Nur Atikah
author_sort	Mustapha, Nur Atikah
title	Comparison of conjugate gradient methods for developing the multiple linear regression model for rice production in Malaysia / Nur Atikah Mustapha
title_short	Comparison of conjugate gradient methods for developing the multiple linear regression model for rice production in Malaysia / Nur Atikah Mustapha
title_full	Comparison of conjugate gradient methods for developing the multiple linear regression model for rice production in Malaysia / Nur Atikah Mustapha
title_fullStr	Comparison of conjugate gradient methods for developing the multiple linear regression model for rice production in Malaysia / Nur Atikah Mustapha
title_full_unstemmed	Comparison of conjugate gradient methods for developing the multiple linear regression model for rice production in Malaysia / Nur Atikah Mustapha
title_sort	comparison of conjugate gradient methods for developing the multiple linear regression model for rice production in malaysia / nur atikah mustapha
granting_institution	Universiti Teknologi MARA
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2018
url	https://ir.uitm.edu.my/id/eprint/41320/1/41320.pdf
_version_	1804889635262824448

Comparison of conjugate gradient methods for developing the multiple linear regression model for rice production in Malaysia / Nur Atikah Mustapha

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