Spline-Fourier’s Method for Modelling Inflation in Indonesia
Regression method is a statistical method for modelling dependent variable with independent variable. Nonparametric regression is an approach to regression analysis that is suitable for data that have an unknown curve shape. Modelling by using nonparametric regression method does not require any ass...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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EDP Sciences
2018-01-01
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| Series: | E3S Web of Conferences |
| Subjects: | |
| Online Access: | https://doi.org/10.1051/e3sconf/20187313003 |
| _version_ | 1818913626553057280 |
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| author | Suparti Suparti Prahutama Alan Santoso Rukun Devi Alvita Rachma |
| author_facet | Suparti Suparti Prahutama Alan Santoso Rukun Devi Alvita Rachma |
| author_sort | Suparti Suparti |
| collection | DOAJ |
| description | Regression method is a statistical method for modelling dependent variable with independent variable. Nonparametric regression is an approach to regression analysis that is suitable for data that have an unknown curve shape. Modelling by using nonparametric regression method does not require any assumptions. Spline and Fourier methods are some of the estimators in nonparametric regression. The spline method requires optimal knots to obtain the best model. The most commonly used method to determine the optimal knots is Generalized Cross Validation (GCV). The Fourier method is a method based on the cosine and sinus series. The Fourier method is particularly suitable for data that experience repetitive patterns. This study modeled the Inflation rate in Indonesia from January 2007 to August 2017. The dependent variable is inflation rate, while the independent variable is time. From the result, linear spline regression estimation with three knots that generates R square of 60%. The best Fourier model is Fourier with K = 100 that generates R square of 80.12%. The best Spline model is with 9 knots generates R square of 87.65%, so, for inflation modelling in Indonesia, the spline regression model generates a simpler model with better R-square than Fourier regression. |
| first_indexed | 2024-12-19T23:33:29Z |
| format | Article |
| id | doaj.art-90b9475bc6874c1bb8f6fd1fb2e7f3f0 |
| institution | Directory Open Access Journal |
| issn | 2267-1242 |
| language | English |
| last_indexed | 2024-12-19T23:33:29Z |
| publishDate | 2018-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj.art-90b9475bc6874c1bb8f6fd1fb2e7f3f02022-12-21T20:01:41ZengEDP SciencesE3S Web of Conferences2267-12422018-01-01731300310.1051/e3sconf/20187313003e3sconf_icenis18_13003Spline-Fourier’s Method for Modelling Inflation in IndonesiaSuparti Suparti0Prahutama Alan1Santoso Rukun2Devi Alvita Rachma3Department of Statistics, Faculty of Science and Mathemathics, Diponegoro UniversityDepartment of Statistics, Faculty of Science and Mathemathics, Diponegoro UniversityDepartment of Statistics, Faculty of Science and Mathemathics, Diponegoro UniversityDepartment of Statistics, Faculty of Science and Mathemathics, Diponegoro UniversityRegression method is a statistical method for modelling dependent variable with independent variable. Nonparametric regression is an approach to regression analysis that is suitable for data that have an unknown curve shape. Modelling by using nonparametric regression method does not require any assumptions. Spline and Fourier methods are some of the estimators in nonparametric regression. The spline method requires optimal knots to obtain the best model. The most commonly used method to determine the optimal knots is Generalized Cross Validation (GCV). The Fourier method is a method based on the cosine and sinus series. The Fourier method is particularly suitable for data that experience repetitive patterns. This study modeled the Inflation rate in Indonesia from January 2007 to August 2017. The dependent variable is inflation rate, while the independent variable is time. From the result, linear spline regression estimation with three knots that generates R square of 60%. The best Fourier model is Fourier with K = 100 that generates R square of 80.12%. The best Spline model is with 9 knots generates R square of 87.65%, so, for inflation modelling in Indonesia, the spline regression model generates a simpler model with better R-square than Fourier regression.https://doi.org/10.1051/e3sconf/20187313003SplineFourierGCVInflation |
| spellingShingle | Suparti Suparti Prahutama Alan Santoso Rukun Devi Alvita Rachma Spline-Fourier’s Method for Modelling Inflation in Indonesia E3S Web of Conferences Spline Fourier GCV Inflation |
| title | Spline-Fourier’s Method for Modelling Inflation in Indonesia |
| title_full | Spline-Fourier’s Method for Modelling Inflation in Indonesia |
| title_fullStr | Spline-Fourier’s Method for Modelling Inflation in Indonesia |
| title_full_unstemmed | Spline-Fourier’s Method for Modelling Inflation in Indonesia |
| title_short | Spline-Fourier’s Method for Modelling Inflation in Indonesia |
| title_sort | spline fourier s method for modelling inflation in indonesia |
| topic | Spline Fourier GCV Inflation |
| url | https://doi.org/10.1051/e3sconf/20187313003 |
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