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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Bibliographic Details
Main Author: Musa, Rosliza
Format: Thesis
Language:English
Published: 2016
Subjects:
Online Access:http://eprints.usm.my/60802/1/24%20Pages%20from%2000001792569.pdf
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Summary: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.