Zobrazeno 1 - 10 of 20 pro vyhledávání: '"Sangjo Lee"'
1
Akademický článek
Change Point Test for the Conditional Mean of Time Series of Counts Based on Support Vector Regression
Autor: Sangyeol Lee, Sangjo Lee
Publikováno v: Entropy, Vol 23, Iss 4, p 433 (2021)
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-valu
Externí odkaz: https://doaj.org/article/6225a06e2b2f43e6ade4eccb579b54d0
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2
Akademický článek
Hybrid CUSUM Change Point Test for Time Series with Time-Varying Volatilities Based on Support Vector Regression
Autor: Sangyeol Lee, Chang Kyeom Kim, Sangjo Lee
Publikováno v: Entropy, Vol 22, Iss 5, p 578 (2020)
This study considers the problem of detecting a change in the conditional variance of time series with time-varying volatilities based on the cumulative sum (CUSUM) of squares test using the residuals from support vector regression (SVR)-generalized
Externí odkaz: https://doaj.org/article/96ecb242c5834888b3b2baa5df51e388
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6
Exponential family QMLE-based CUSUM test for integer-valued time series
Autor: Sangjo Lee, Sangyeol Lee
Publikováno v: Communications in Statistics - Simulation and Computation. 52:2022-2043
This study considers testing for parameter changes in integer-valued time series models based on one parameter exponential family quasi-maximum likelihood estimates. We employ the cumulative sum (C...
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c162965844856c339c876827f40b6492
https://doi.org/10.1080/03610918.2021.1897620
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8
Change Point Test for the Conditional Mean of Time Series of Counts Based on Support Vector Regression
Autor: Sangjo Lee, Sangyeol Lee
Publikováno v: Entropy, Vol 23, Iss 433, p 433 (2021)
Entropy
Volume 23
Issue 4
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-valu
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::98d9d4f6be90e2b560f344cf30a0c115
https://pubmed.ncbi.nlm.nih.gov/33917192
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9
Hybrid CUSUM Change Point Test for Time Series with Time-Varying Volatilities Based on Support Vector Regression
Autor: Chang Kyeom Kim, Sangyeol Lee, Sangjo Lee
Publikováno v: Entropy
Volume 22
Issue 5
Entropy, Vol 22, Iss 578, p 578 (2020)
This study considers the problem of detecting a change in the conditional variance of time series with time-varying volatilities based on the cumulative sum (CUSUM) of squares test using the residuals from support vector regression (SVR)-generalized
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::de5eecb521583fd14b7fd96d586fdbf9
https://pubmed.ncbi.nlm.nih.gov/33286350
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