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

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.