Model Regresi Robust dengan Metode Estimasi M, Estimasi S dan Estimasi MM untuk Produksi Beras di Nusa Tenggara Timur - Katarina K. Gasul; Astri Atti; Maria A. Kleden (Hasanuddin University, 2023)
In the regression analysis, the amount of rice production that far exceeds the general production can be categorized as outlier data. The existence of outliers causes the use of the least squares method to estimate parameters to be deemed inappropriate. To deal with outlier data, it is necessary to use methods that are robust or resistant to outlier data. Robust is defined as insensitivity or rigidity to outlier data. The purpose of this study is to obtain a robust regression model using the M estimation, S estimation and MM estimation methods and determine the factors that have a significant effect on rice production in East Nusa Tenggara Province. The model using the S estimation method is the best model, namely y = 3,895.023 + 1.870 X1 - 60.926 X5 and the factors that have a significant effect on rice production are harvested area and air temperature.