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...
محفوظ في:
| المؤلف الرئيسي: | |
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| التنسيق: | أطروحة |
| اللغة: | English |
| منشور في: |
2016
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://eprints.usm.my/60802/1/24%20Pages%20from%2000001792569.pdf |
| الوسوم: |
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| الملخص: | 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. |
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