PENDETEKSIAN OUTLIER PADA REGRESI LOGISTIK DENGAN MENGGUNAKAN TEKNIK TRIMMED MEANS
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Date
2017-01-20
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Abstract
This article discusses the outlier of logistic regression. The estimator is obtained
through maximum likelihood method. Then numerical approach of Newton-Raphson
method is applied. Furthurmore the coefficient of determination R2 is evaluated to
interprete the dependent variables which are explained by the independent variables.
The next step is the outlier detection by trimming of outlier estimate data in the
side X, this technique is an idea from trimmed means. Trimming of data affects the
regression model and upgrade the coefficient of determination R2.
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Keywords
Logistic regression model, outlier, trimmed means, maximum likelihood method, Newton-Raphson method, coefficient of determination R2