Estimation Non Linier Model with Genetic Algoritma

In general, estimates in Model Non Linier method using OLS (Ordinary Least Square) or ML (Maximum Likelihood) with conventional algorithms method such as Gause-Newton; Rhapson-Newton, Levenberg-Marquardt; Berndt, Hall, Hall & Hausman or the quadratic Hill-Climbing. These Algorithms will not produce a global minimum / maximum. In this paper will explain the new approach, namely Genetic Algorithm to ensure global maximum/ minimum. Monte Carlo simulation is used to guarantee the results Robusness estimates. Computing used MATLAB.

Download if you want to get the full paper: Genetic Algoritma.pdf

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NonLinier Estimation using OLS and Max Likelihood

Paper will report the results experiment model nonlinear to estimate production function Cobb-Douglas and CES using the Least Square method Nonlinear and Non-Linier Maximum Likelihood. Model estimation method linier used non-conventional approach Algorithm Gause-Newton; Rhapson-Newton, Levenberg-Marquardt; Berndt, Hall, Hall & Hausman or the quadratic Hill-Climbing. In this paper will describe the approach. Monte Carlo simulation is used to guarantee the results Robusness estimates. Computing used MATLAB.

Download if you want to complete any posts [Non Linier.pdf] dan [Lampiran]

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Ordinary Least Square Estimation in Linier Model and Monte Carlo Simulation

Ordinary Least Square Estimation in Linier Model and Monte Carlo Simulation. In general methods of estimation in Model Linier used OLS (Ordinary Least Square) or ML (Maximum Likelihood). In this Paper describes theoretically how the estimate methods are. Monte Carlo simulation is used to guarantee the results robusness estimates. Computing used MATLAB. Econometric. Ekonometrik

Download if you want to get the full paper: (1)cover.pdf; (2)daftar-isi.pdf; (3)isi.pdf

Keyword: Econometric, Ekonometrik, Estimation, MATLAB, Maximum Likelihood, Monte Carlo, OLS, Ordinary Least Square, Simulasi, Simulation.

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