Authors:

NI MADE METTA ASTARI, NI LUH PUTU SUCIPTAWATI, I KOMANG GDE SUKARSA

Abstract:

“Statistical analysis which aims to analyze a linear relationship between the independent variable and the dependent variable is known as regression analysis. To estimate parameters in a regression analysis method commonly used is the Ordinary Least Square (OLS). But the assumption is often violated in the OLS, the assumption of normality due to one outlier. As a result of the presence of outliers is parameter estimators produced by the OLS will be biased. Bootstrap Residual is a bootstrap method that is applied to the residual resampling process. The results showed that the residual bootstrap method is only able to overcome the bias on the number of outliers 5% with 99% confidence intervals. The resulting parameters estimators approach the residual bootstrap values ??OLS initial allegations were also able to show that the bootstrap is an accurate prediction tool.”

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PDF:

https://jurnal.harianregional.com/mtk/full-11994

Published

2014-11-28

How To Cite

ASTARI, NI MADE METTA; SUCIPTAWATI, NI LUH PUTU; SUKARSA, I KOMANG GDE. PENERAPAN METODE BOOTSTRAP RESIDUAL DALAM MENGATASI BIAS PADA PENDUGA PARAMETER ANALISIS REGRESI.E-Jurnal Matematika, [S.l.], v. 3, n. 4, p. 130 - 137, nov. 2014. ISSN 2303-1751. Available at: https://jurnal.harianregional.com/mtk/id-11994. Date accessed: 28 Aug. 2025. doi:https://doi.org/10.24843/MTK.2014.v03.i04.p075.

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Issue

Vol 3 No 4 (2014)

Section

Articles

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