A Weighted Least Squares Estimation Of The Polynomial Regression Model On Paddy Production For The Muda Agriculture And Development Authority (Mada) Area
The curvilinear relationship between a dependent variable and several independent variables can be represented by a polynomial regression model. This model is used to study the relationship between response variable and predictor variable which contain square and higher-order term. Polynomial reg...
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my-usm-ep.608022024-07-09T05:03:23Z A Weighted Least Squares Estimation Of The Polynomial Regression Model On Paddy Production For The Muda Agriculture And Development Authority (Mada) Area 2016-01 Musa, Rosliza QA1 Mathematics (General) The curvilinear relationship between a dependent variable and several independent variables can be represented by a polynomial regression model. This model is used to study the relationship between response variable and predictor variable which contain square and higher-order term. Polynomial regression model is a special case of multiple regression model. The building of polynomial regression model has the same characteristics as multiple linear regressions in term of parameter estimation, regression inference, variable selection and model diagnostic. Weighted least square estimation is used as a remedy for non-constant variance. This study used polynomial regression model with weighted least square estimation to investigate paddy production of different paddy lots based on environmental and cultivation characteristics in Muda Agriculture and Development Authority (MADA) area. 2016-01 Thesis http://eprints.usm.my/60802/ http://eprints.usm.my/60802/1/24%20Pages%20from%2000001792569.pdf application/pdf en public masters Perpustakaan Hamzah Sendut Pusat Pengajian Sains Matematik |
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English |
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QA1 Mathematics (General) |
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QA1 Mathematics (General) Musa, Rosliza A Weighted Least Squares Estimation Of The Polynomial Regression Model On Paddy Production For The Muda Agriculture And Development Authority (Mada) Area |
description |
The curvilinear relationship between a dependent variable and several independent
variables can be represented by a polynomial regression model. This model is used to
study the relationship between response variable and predictor variable which contain
square and higher-order term. Polynomial regression model is a special case of multiple
regression model. The building of polynomial regression model has the same
characteristics as multiple linear regressions in term of parameter estimation, regression
inference, variable selection and model diagnostic. Weighted least square estimation is
used as a remedy for non-constant variance. This study used polynomial regression
model with weighted least square estimation to investigate paddy production of
different paddy lots based on environmental and cultivation characteristics in Muda
Agriculture and Development Authority (MADA) area. |
format |
Thesis |
qualification_level |
Master's degree |
author |
Musa, Rosliza |
author_facet |
Musa, Rosliza |
author_sort |
Musa, Rosliza |
title |
A Weighted Least Squares Estimation Of The Polynomial Regression Model On Paddy Production For The Muda Agriculture And Development Authority (Mada) Area |
title_short |
A Weighted Least Squares Estimation Of The Polynomial Regression Model On Paddy Production For The Muda Agriculture And Development Authority (Mada) Area |
title_full |
A Weighted Least Squares Estimation Of The Polynomial Regression Model On Paddy Production For The Muda Agriculture And Development Authority (Mada) Area |
title_fullStr |
A Weighted Least Squares Estimation Of The Polynomial Regression Model On Paddy Production For The Muda Agriculture And Development Authority (Mada) Area |
title_full_unstemmed |
A Weighted Least Squares Estimation Of The Polynomial Regression Model On Paddy Production For The Muda Agriculture And Development Authority (Mada) Area |
title_sort |
weighted least squares estimation of the polynomial regression model on paddy production for the muda agriculture and development authority (mada) area |
granting_institution |
Perpustakaan Hamzah Sendut |
granting_department |
Pusat Pengajian Sains Matematik |
publishDate |
2016 |
url |
http://eprints.usm.my/60802/1/24%20Pages%20from%2000001792569.pdf |
_version_ |
1804888999696793600 |