Teknosains: Media Informasi Sains dan Teknologi
Vol 13 No 2 (2019): JULI

ESTIMATOR KERNEL PADA REGRESI NONPARAMETRIK MENGGUNAKAN PENDEKATAN FUNGSI KERNEL GAUSSIAN

Alwi, Wahidah (Unknown)
Sauddin, Adnan (Unknown)
Nirmala, Nirmala (Unknown)



Article Info

Publish Date
16 Jul 2019

Abstract

The study by using the data to model a state (variable) in the statistical analysis usually requires certain assumptions in order to use the analysis results in accordance with the actual situation. This study uses a nonparametric procedure to estimate a function in which the function does not lead to a certain model of a particular function. The main problem of regression analysis is to determine the shape estimation. One approach that can be used to determine  is a kernel estimator with a Gaussian kernel approach. The data used is data that the percentage of women aged 15-49 who have been married according to the last birth attendants in South Sulawesi with the gynecologist predictor variables (), general practitioners (), midwives (), and the response variable () the number of women who have been married according to the last birth attendants. Methods GCV (Generalized Cross Validation) is used to obtain optimal bandwidth that is at ,  and = 25 with value GCV is . The optimum value is the maximum value of the percentage of women aged  who have been married according to the last birth attendants in South Sulawesi.

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Journal Info

Abbrev

teknosains

Publisher

Subject

Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Physics

Description

Teknosains: Media Informasi Sains dan Teknologi is a peer-reviewed journal that publishes three times a year (January-April, May-August, and September-December) on articles concerning all areas of science and technology in both theoretical and applied research. The below-mentioned areas are just ...