Estimasi Parameter Regresi Linier Sederhana Menggunakan Prosedur Cochrane-Orcutt, Hildreth-Lu dan First Differences Pada Metode Durbin Watson - Purba, Switamy Angnitha; Chrisinta, Debora; Simarmata, Justin Eduardo (Jurusan Matematika FMIPA UNM, 2023)
This study aims to examine the problem of autocorrelation, simple regression analysis with errorsfollowing the form of first-order autoregressive, Durbin Watson method using the Cochrane-Orcutt,Hildreth-Lu procedures and first differences in overcoming autocorrelation. The occurrence ofautocorrelation causes the alleged regression parameter with ordinary least square (OLS) not to producethe actual value. Therefore, to obtain the actual parameters applied Durbin watson method with all threeprocedures. Based on the data used in this thesis quoted from the book Applied Linear Statistical ModelsFifth Edition, the best procedure is given by Hildreth-Lu because it produces the smallest mean squareerror (MSE) value namely 0,204. This is because, the process of estimating the autocorrelation coefficientis based on iterations until a minimum sum square error (SSE) value is found.