Parameter: Journal of Statistics
Vol. 2 No. 3 (2022)

Modeling of Poverty Level in Central Sulawesi Using Nonparametric Kernel Regression Analysis Approach

Nur Sakinah (Universitas Tadulako)
Nurfitra (Universitas Tadulako)
Nurmasyita Ihlasia (Universitas Tadulako)
Lilies Handayani (Universitas Tadulako)

Article Info

Publish Date
31 Dec 2022

Abstract

Poverty is defined as a person's inability to meet their basic needs. The level of poverty that exists can be used to assess the good or bad of a country's economy. The kernel regression method is used in this study to model the poverty rate in Central Sulawesi in 2020. According to the findings of this study, comparing poverty rate predictions for the Gaussian Kernel function and the Epanechnikov Kernel function with optimal bandwidth can be said to use different kernel functions with optimal bandwidth for each - each of these kernel functions will produce the same curve estimate. So, in kernel regression, the selection of the optimal bandwidth value is more important than the selection of the kernel function. Because of the use of various kernels functions with optimal bandwidth values results in almost the same curve estimation.

Copyrights © 2022




Citation Download
RIS
EndNote, Reference Manager, ProCite
BibTex
Latex, Jabref
Original Source
Download Original
Google Scholar
Check in Google Scholar
Journal Info
Parameter: Journal of Statistics
Website

Abbrev

parameter

Publisher

Universitas Tadulako

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Mathematics

Description

Parameter: Journal of Statistics is a refereed journal committed to original research articles, reviews and short communications of Statistics and its ...