Open AccessThe Effect of Human Development Index on Poverty Model in Indonesia using Penalized Basis Spline Nonparametric Regression.
Author(s) -
Nurul Hasanah,
Samsul Bahri,
Nurul Fitriyani
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1115/1/012055
Subject(s) - smoothing spline , knot (papermaking) , mathematics , spline (mechanical) , nonparametric statistics , nonparametric regression , econometrics , smoothing , statistics , single index model , regression , poverty , regression analysis , spline interpolation , economics , engineering , economic growth , chemical engineering , structural engineering , bilinear interpolation
Poverty is an issue of special concern to various countries in the world, including Indonesia. One factor that can affect poverty is the Human Development Index (HDI). The aim of this study is to model of the problem of poverty based on HDI. Using nonparametric spline regression was used with the penalized basis spline (PB-Spline) approach, which can overcome the problem of selecting many knot points and the location of knots in spline regression. This study was obtained three models, i.e. model with one knot point, model with two knot points, and model with three knot points. Based on indicators of the value of Generalized Cross Validation (GCV) and the value of Mean Square Error (MSE), the best model was a model with three knots, with smoothing parameter value of 1000, 11.26236 value of GCV and 11.08420 value of MSE.