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Hisintus Suban Hurint
Mahasiswa Program Studi Statistika FMIPA Universitas Mulawarman
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Other

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Metode Regresi Robust Dengan Estimasi Method of Moment (Estimasi-MM) Pada Regresi Linier Berganda Hisintus Suban Hurint; Ika Purnamasari; Memi Nor Hayati
EKSPONENSIAL Vol 7 No 2 (2016)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Method of Ordinary Least Square (OLS) on the regression analysis is a method which is often used to estimate the parameters. In the OLS method, there are several assumptions that must be fulfilled, these assumptions are often not fulfilled when the data contains outlier, so need a method that are robust to the presence of outliers. In this research, studied method of robust regression with MM-estimation. MM-estimation is a combination of estimation methods that have a high breakdown point, namely the Scale estimation(S-estimation) and Least Trimmed Square estimation (LTS estimation) and the method that have higher efficiency point, namely the Maximum Likelihood Type estimation (M-estimation). The first step in the MM-estimation is to find the S-estimator, then set the parameter regression using the M-estimation. The purpose of this study was to determine the effect of price index of foodstuffs ( ), the price index of education ), and the price index of health ) to the CPI for the province of east borneo, where the CPI data contains outliers, namely observation to 13, 31,and 32.
Co-Authors Ika Purnamasari Memi Nor Hayati