Edu Research


MODEL REGRESI BINOMIAL NEGATIF TERBOBOTI GEOGRAFIS UNTUK DATA KEMATIAN BAYI

Afri, Lusi Eka ( Program Studi Pendidikan Matematika Fakultas Keguruan dan Ilmu Pendidikan Universitas Pasir Pengaraian)



Article Info

Publish Date
15 Aug 2013

Abstract

Negative binomial regression model is used to overcome theoverdispersion in Poisson regression model. This model can be used to model therelationship of the infant mortality and the factors incidence. Geographicalconditions, socio cultural and economic differ one of location another locationcauses the factors that influence infant mortality is different locally.Geographically Weighted Negative Binomial Regression (GWNBR) is one ofmethods for modeling that count data have spatial heterogeneity andoverdispersion. The basic idea of this model considers of geography or locationas the weight in parameter estimation. The parameter estimator is obtained fromIteratively Newton Raphson method. This research will determine the factors thatinfluence infant mortality. GWNBR model with a weighting adaptive bi-squarekernel function classifies regency/city in East Java into 16 groups based on thefactors that significantly influence the number of infant mortality. This model isbetter used to analyze the number of infant mortality in East Java in 2008 due toa smallest deviance value.

Copyrights © 2013






Journal Info

Abbrev

fkip

Publisher

Subject

Education

Description

Edu Research diterbitkan dengan maksud untuk mengumpulkan karya ilmiah dari hasil penelitian dan/atau yang setara dengan hasil penelitian dalam bidang kependidikan dan mempublikasikan karya ilmiah tersebut. Edu Research terbit dua kali dalam setahun pada bulan Juni dan Desember. Isi artikel yang ...