Open AccessModeling with Mixed Kernel, Spline Truncated and Fourier Series on Human Development Index in East Java
Author(s) -
Narita Yuri Adrianingsih,
I Nyoman Budiantara,
Jerry Dwi Trijoyo Purnomo
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/1115/1/012024
Subject(s) - mathematics , fourier series , nonparametric statistics , spline (mechanical) , nonparametric regression , statistics , smoothing spline , estimator , regression analysis , kernel (algebra) , kernel regression , econometrics , mathematical analysis , spline interpolation , engineering , structural engineering , combinatorics , bilinear interpolation
The pattern of the relationship between the response variable and the unknown predictor can be determined using a nonparametric regression approach. Nonparametric regression allows it to be used for response variables following different curves between one variable and another. In this regression, there are several types of approaches including the kernel, spline, and Fourier series. In its use, there is not only one type of approach, but can be in the form of a mixture, such as a mixture of a spline and Fourier series, a kernel and a Fourier series, and so on. In this study, in modeling the HDI cases in East Java Province, nonparametric regression mixed kernels, Spline Truncated, and Fourier series were used. The results of research that have been applied to HDI in East Java with the predictor variables for APM SMA, Morbidity, and GRDP per Capita are using the mixed kernel, Spline Truncated, and Fourier series nonparametric regression approach with three-knot points and three oscillations. Good because the coefficient of determination of the estimator is 75.1041%.