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All Journal JMathCos (Journal of Mathematics, Computation, and Statistics)
Switamy Angnitha Purba
Universitas Timor

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Estimasi Parameter Regresi Linier Sederhana Menggunakan Prosedur Cochrane-Orcutt, Hildreth-Lu dan First Differences Pada Metode Durbin Watson Switamy Angnitha Purba; Debora Chrisinta; Justin Eduardo Simarmata
Journal of Mathematics Computations and Statistics Vol 6, No 2 (2023): Oktober
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v6i2.51177

Abstract

This study aims to examine the problem of autocorrelation, simple regression analysis with errors following the form of first-order autoregressive, Durbin Watson method using the Cochrane-Orcutt, Hildreth-Lu procedures and first differences in overcoming autocorrelation. The occurrence of autocorrelation causes the alleged regression parameter with ordinary least square (OLS) not to produce the actual value. Therefore, to obtain the actual parameters applied Durbin watson method with all three procedures. Based on the data used in this thesis quoted from the book Applied Linear Statistical Models Fifth Edition, the best procedure is given by Hildreth-Lu because it produces the smallest mean square error (MSE) value. This is because, the process of estimating the autocorrelation coefficient is based on iterations until a minimum sum square error (SSE) value is found.
Co-Authors Debora Chrisinta Simarmata, Justin Eduardo