Estimating multiple linear regression parameters using term omission method
DOI:
https://doi.org/10.21533/pen.v8.i4.1397Abstract
In this paper, we introduce a new method to estimate multiple linear regression parameters, namely Multiple Term Omission (MTO). Then, we compare its performance with other three methods: Ordinary Least Square (OLS), Maximum Likelihood (ML) and Bayesian Model using several criteria, such as Mean Average Deviation (MAD), Mean Absolute Percentage Error (MAPE) and Root Mean Square Error standard (RMSE). MTO method has the finest consequences as compared to the other methods for the experimented data.
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