ANALISIS REGRESI NONPARAMETRIK SPLINE MULTIVARIAT UNTUK PEMODELAN INDIKATOR KEMISKINAN DI INDONESIA
ABSTRACT: The aim of this
study is to obtain statistics models which explain the relationship between
variables that influence the poverty indicators in Indonesia using multivariate
spline nonparametric regression method. Spline is a nonparametric regression
estimation method that is automatically search for its estimation wherever the
data pattern move and thus resulting in model which fitted the data. This study,
uses data from survey of Social Economy National (Susenas) and survey of
Employment National (Sakernas) of 2013 from the publication of the Central
Bureau of Statistics (BPS). This study yields two models which are the best
model from two used response variables. The criterion uses to select the best
model is the minimum Generalized Cross Validation (GCV). The best spline model obtained
is cubic spline model with five optimal knots.
Penulis: Desak Ayu Wiri Astiti
Kode Jurnal: jpmatematikadd160175
