Change Point Test for the Conditional Mean of Time Series of Counts Based on Support Vector Regression
This study considers support vector regression (SVR) and twin SVR (TSVR) for the time series of counts, wherein the hyper parameters are tuned using the particle swarm optimization (PSO) method. For prediction, we employ the framework of integer-valued generalized autoregressive conditional heterosk...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-04-01
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| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/23/4/433 |
| _version_ | 1827695702637019136 |
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| author | Sangyeol Lee Sangjo Lee |
| author_facet | Sangyeol Lee Sangjo Lee |
| author_sort | Sangyeol Lee |
| collection | DOAJ |
| description | This study considers support vector regression (SVR) and twin SVR (TSVR) for the time series of counts, wherein the hyper parameters are tuned using the particle swarm optimization (PSO) method. For prediction, we employ the framework of integer-valued generalized autoregressive conditional heteroskedasticity (INGARCH) models. As an application, we consider change point problems, using the cumulative sum (CUSUM) test based on the residuals obtained from the PSO-SVR and PSO-TSVR methods. We conduct Monte Carlo simulation experiments to illustrate the methods’ validity with various linear and nonlinear INGARCH models. Subsequently, a real data analysis, with the return times of extreme events constructed based on the daily log-returns of Goldman Sachs stock prices, is conducted to exhibit its scope of application. |
| first_indexed | 2024-03-10T12:31:53Z |
| format | Article |
| id | doaj.art-6225a06e2b2f43e6ade4eccb579b54d0 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-10T12:31:53Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-6225a06e2b2f43e6ade4eccb579b54d02023-11-21T14:34:24ZengMDPI AGEntropy1099-43002021-04-0123443310.3390/e23040433Change Point Test for the Conditional Mean of Time Series of Counts Based on Support Vector RegressionSangyeol Lee0Sangjo Lee1Department of Statistics, Seoul National University, Seoul 08826, KoreaDepartment of Statistics, Seoul National University, Seoul 08826, KoreaThis study considers support vector regression (SVR) and twin SVR (TSVR) for the time series of counts, wherein the hyper parameters are tuned using the particle swarm optimization (PSO) method. For prediction, we employ the framework of integer-valued generalized autoregressive conditional heteroskedasticity (INGARCH) models. As an application, we consider change point problems, using the cumulative sum (CUSUM) test based on the residuals obtained from the PSO-SVR and PSO-TSVR methods. We conduct Monte Carlo simulation experiments to illustrate the methods’ validity with various linear and nonlinear INGARCH models. Subsequently, a real data analysis, with the return times of extreme events constructed based on the daily log-returns of Goldman Sachs stock prices, is conducted to exhibit its scope of application.https://www.mdpi.com/1099-4300/23/4/433time series of countsINGARCH modelSVR and TSVR with PSOchange point detectionCUSUM test |
| spellingShingle | Sangyeol Lee Sangjo Lee Change Point Test for the Conditional Mean of Time Series of Counts Based on Support Vector Regression Entropy time series of counts INGARCH model SVR and TSVR with PSO change point detection CUSUM test |
| title | Change Point Test for the Conditional Mean of Time Series of Counts Based on Support Vector Regression |
| title_full | Change Point Test for the Conditional Mean of Time Series of Counts Based on Support Vector Regression |
| title_fullStr | Change Point Test for the Conditional Mean of Time Series of Counts Based on Support Vector Regression |
| title_full_unstemmed | Change Point Test for the Conditional Mean of Time Series of Counts Based on Support Vector Regression |
| title_short | Change Point Test for the Conditional Mean of Time Series of Counts Based on Support Vector Regression |
| title_sort | change point test for the conditional mean of time series of counts based on support vector regression |
| topic | time series of counts INGARCH model SVR and TSVR with PSO change point detection CUSUM test |
| url | https://www.mdpi.com/1099-4300/23/4/433 |
| work_keys_str_mv | AT sangyeollee changepointtestfortheconditionalmeanoftimeseriesofcountsbasedonsupportvectorregression AT sangjolee changepointtestfortheconditionalmeanoftimeseriesofcountsbasedonsupportvectorregression |