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Application of Robust Regression in Production of Maize
Arni Natasha Binti Azmar
Supervisor: Assoc. Prof. Dr. Norizan Binti Mohamed
Bachelor of Science (Financial Mathematic)
School of Informatics and Applied Mathematics
Maize is a kind of cereal and it used as a food source of human and animal. This study
discusses the use of robust regression analysis in maize production data. SAS software
has been used in identifying outlier in maize production data. In regression analysis, the
use of least square method would not suitable in solving problem containing outlier. This
study needs a parameter estimation method which is robust where the value of estimation
is not much affected by small changes in the data. The estimators used in this study are
M, MM, S and LTS estimation. The comparison between estimators of robust regression
is performed to get the best robust regression and to construct the best regression model.
Next, the data were contaminated by 10%, 20% and 30% to determine the robustness
of the model. The result show that the model still robust even though the data were
contaminated.
794 | UMT UNDERGRADUATE RESEARCH DAY 2018