Modeling Poverty Percentages in the Papua Islands using Fourier Series in Nonparametric Regression Multivariable

N. P.A.M. Mariati, I. N. Budiantara*, V. Ratnasari

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

5 Citations (Scopus)

Abstract

Nonparametric regression has high flexibility in estimating the regression curve. Estimation techniques that are quite popular in nonparametric regression are Fourier Series estimators. Fourier series are trigonometric polynomials that have flexibility, so they can adapt effectively to the local nature of data. This Fourier series estimator is generally used if the data investigated by the pattern is unknown and there is a tendency for repetitive patterns to follow the trend line. The purpose of this study is to examine Fourier Series estimates and apply to cases of poverty in the Papua Islands. The Papua Islands which consist of 2 Provinces namely Papua Province and West Papua Province. Papua Province ranked first and West Papua Province ranked second in poverty in Indonesia. Based on nonparametric regression multivariable modeling using Fourier series, this model is good. This can be seen from the value obtained by Generalized Cross Validation (GCV) = 80, 76, Mean Square Error (MSE) is 18, 31 and R2=78, 16%.

Original languageEnglish
Article number012071
JournalJournal of Physics: Conference Series
Volume1397
Issue number1
DOIs
Publication statusPublished - 19 Dec 2019
Event6th International Conference on Research, Implementation, and Education of Mathematics and Science, ICRIEMS 2019 - Yogyakarta, Indonesia
Duration: 12 Jul 201913 Jul 2019

Fingerprint

Dive into the research topics of 'Modeling Poverty Percentages in the Papua Islands using Fourier Series in Nonparametric Regression Multivariable'. Together they form a unique fingerprint.

Cite this