CD Skripsi

Pendeteksian Outlier Pada Regresi Logistik Dengan Menggunakan Teknik Trimmed Means

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This final project discusses the outlier of logistic regression. The estimator is obtained through maximum likelihood method. Then numerical approach of which is named Newton-Raphson method is applied. Furthurmore goodness of fitting by using Hosmer and Lemeshow test and the coefficient of determination R2 is evaluated to be interprete the predictor variables which are explained by the respond variables. The next step is 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. The compute and data analysis by using R program version 3.2.5
Keywords: Logistic regression model, outlier, trimmed means, maximum likelihood method, Newton-Raphson method, Hosmer and Lemeshow test, coefficient of determination R2

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

03 03.117 (0098)

Penerbit

Pekanbaru : Universitas Riau - FMIPA - Matematika., 2017

Deskripsi Fisik

xii, 37 hlm.; ill.; 29 cm

Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

03 03.117 (0098)

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

MATEMATIKA

Info Detail Spesifik

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Pernyataan Tanggungjawab

DODY

Versi lain/terkait

Lampiran Berkas

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