MODEL REGRESI BINOMIAL NEGATIF TERBOBOTI GEOGRAFIS UNTUK DATA KEMATIAN BAYI - Afri, Lusi Eka (Edu Research, 2013)
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.