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Sangyeol Lee
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2020 – today
- 2023
- [j35]Liang-Ching Lin, Meihui Guo, Sangyeol Lee:
Monitoring photochemical pollutants based on symbolic interval-valued data analysis. Adv. Data Anal. Classif. 17(4): 897-926 (2023) - [j34]Sangyeol Lee, Dongwon Kim
, Byungsoo Kim:
Modeling and inference for multivariate time series of counts based on the INGARCH scheme. Comput. Stat. Data Anal. 177: 107579 (2023) - [j33]Sangyeol Lee, Sangjo Lee:
Exponential family QMLE-based CUSUM test for integer-valued time series. Commun. Stat. Simul. Comput. 52(5): 2022-2043 (2023) - [j32]Chang Kyeom Kim, Sangyeol Lee
:
Conditional quantile change test for time series based on support vector regression. Commun. Stat. Simul. Comput. 52(11): 5567-5584 (2023) - 2022
- [j31]Sangyeol Lee, Simos G. Meintanis, Charl Pretorius
:
Monitoring procedures for strict stationarity based on the multivariate characteristic function. J. Multivar. Anal. 189: 104892 (2022) - [j30]Sangyeol Lee, Sangjo Lee, Chang Kyeom Kim:
One-class classification-based monitoring for the mean and variance of time series. Qual. Reliab. Eng. Int. 38(5): 2548-2565 (2022) - 2021
- [j29]Hanwool Kim, Sangyeol Lee
:
On residual CUSUM statistic for PINAR(1) model in statistical design and diagnostic of control chart. Commun. Stat. Simul. Comput. 50(5): 1290-1314 (2021) - [j28]Cathy W. S. Chen
, Sangyeol Lee
, Khemmanant Khamthong:
Bayesian inference of nonlinear hysteretic integer-valued GARCH models for disease counts. Comput. Stat. 36(1): 261-281 (2021) - [j27]Byungsoo Kim, Sangyeol Lee
, Dongwon Kim:
Robust Estimation for Bivariate Poisson INGARCH Models. Entropy 23(3): 367 (2021) - [j26]Sangyeol Lee, Sangjo Lee:
Change Point Test for the Conditional Mean of Time Series of Counts Based on Support Vector Regression. Entropy 23(4): 433 (2021) - 2020
- [j25]Sangyeol Lee, Sangjo Lee, Miteum Moon:
Hybrid change point detection for time series via support vector regression and CUSUM method. Appl. Soft Comput. 89: 106101 (2020) - [j24]Byungsoo Kim, Sangyeol Lee
:
Robust Change Point Test for General Integer-Valued Time Series Models Based on Density Power Divergence. Entropy 22(4): 493 (2020) - [j23]Sangyeol Lee, Chang Kyeom Kim, Sangjo Lee:
Hybrid CUSUM Change Point Test for Time Series with Time-Varying Volatilities Based on Support Vector Regression. Entropy 22(5): 578 (2020) - [j22]Sangyeol Lee
, Dongwon Kim:
Monitoring Parameter Change for Time Series Models of Counts Based on Minimum Density Power Divergence Estimator. Entropy 22(11): 1304 (2020) - [j21]Sangyeol Lee
, Chang Kyeom Kim, Dongwuk Kim:
Monitoring Volatility Change for Time Series Based on Support Vector Regression. Entropy 22(11): 1312 (2020)
2010 – 2019
- 2019
- [j20]Youngmi Lee, Sangyeol Lee
:
On causality test for time series of counts based on poisson ingarch models with application to crime and temperature data. Commun. Stat. Simul. Comput. 48(6): 1901-1911 (2019) - [j19]Hanwool Kim, Sangyeol Lee
:
Improved CUSUM monitoring of Markov counting process with frequent zeros. Qual. Reliab. Eng. Int. 35(7): 2371-2394 (2019) - [p4]Sangyeol Lee:
Cumulative Residual Entropy-Based Goodness of Fit Test for Location-Scale Time Series Model. Structural Changes and their Econometric Modeling 2019: 105-115 - 2018
- [j18]Haejune Oh, Sangyeol Lee:
On score vector- and residual-based CUSUM tests in ARMA-GARCH models. Stat. Methods Appl. 27(3): 385-406 (2018) - [p3]Haejune Oh, Sangyeol Lee:
On Parameter Change Test for ARMA Models with Martingale Difference Errors. Predictive Econometrics and Big Data 2018: 246-254 - 2017
- [j17]Sangyeol Lee, Minjo Kim:
On Entropy Test for Conditionally Heteroscedastic Location-Scale Time Series Models. Entropy 19(8): 388 (2017) - [p2]Cathy W. S. Chen, Khemmanant Khamthong, Sangyeol Lee:
Structural Breaks of CAPM-type Market Model with Heteroskedasticity and Quantile Regression. Robustness in Econometrics 2017: 111-134 - [p1]Yingshi Xu, Sangyeol Lee:
Quantile Forecasting of PM10 Data in Korea Based on Time Series Models. Robustness in Econometrics 2017: 587-598 - 2016
- [j16]Minjo Kim, Sangyeol Lee
:
Nonlinear expectile regression with application to Value-at-Risk and expected shortfall estimation. Comput. Stat. Data Anal. 94: 1-19 (2016) - [j15]Cathy W. S. Chen
, Sangyeol Lee
:
Generalized Poisson autoregressive models for time series of counts. Comput. Stat. Data Anal. 99: 51-67 (2016) - [j14]Cathy W. S. Chen
, Sangyeol Lee
, Shu-Yu Chen:
Local non-stationarity test in mean for Markov switching GARCH models: an approximate Bayesian approach. Comput. Stat. 31(1): 1-24 (2016) - [c5]Myounghwan Choi, Jeong-Yeol Ahn, Dae-Jin Park, Yujin Jeong, Sangyeol Lee, Sanghyub Lee, Dong-Il Cho, Yong-Sook Goo, Kyo-In Koo:
Adaptive Forward-Reverse Filter using Interpolation Methods for Artifact Suppression in Retinal Prostheses. PECCS 2016: 105-109 - 2015
- [j13]Sangyeol Lee
, Haejune Oh:
Entropy test and residual empirical process for autoregressive conditional duration models. Comput. Stat. Data Anal. 86: 1-12 (2015) - 2014
- [j12]Sangyeol Lee
:
Goodness of fit test for discrete random variables. Comput. Stat. Data Anal. 69: 92-100 (2014) - [j11]Jiwon Kang, Sangyeol Lee
:
Minimum density power divergence estimator for Poisson autoregressive models. Comput. Stat. Data Anal. 80: 44-56 (2014) - [j10]Byungsoo Kim, Sangyeol Lee
:
Minimum density power divergence estimator for covariance matrix based on skew $$t$$ t distribution. Stat. Methods Appl. 23(4): 565-575 (2014) - [c4]Sangyeol Lee
, Jiyeon Lee:
Residual Based Cusum Test for Parameter Change in AR-GARCH Models. TES 2014: 101-111 - 2013
- [j9]Sangyeol Lee
:
A maximum entropy type test of fit: Composite hypothesis case. Comput. Stat. Data Anal. 57(1): 59-67 (2013) - [j8]Byungsoo Kim, Sangyeol Lee
:
Robust estimation for the covariance matrix of multivariate time series based on normal mixtures. Comput. Stat. Data Anal. 57(1): 125-140 (2013) - [j7]Liang-Ching Lin, Sangyeol Lee
, Meihui Guo:
Goodness-of-fit test for stochastic volatility models. J. Multivar. Anal. 116: 473-498 (2013) - 2011
- [j6]Sangyeol Lee
, Ilia Vonta
, Alex Karagrigoriou
:
A maximum entropy type test of fit. Comput. Stat. Data Anal. 55(9): 2635-2643 (2011) - [j5]Okyoung Na, Youngmi Lee, Sangyeol Lee
:
Monitoring parameter change in time series models. Stat. Methods Appl. 20(2): 171-199 (2011) - 2010
- [j4]Sangyeol Lee
, Chi Tim Ng:
Trimmed portmanteau test for linear processes with infinite variance. J. Multivar. Anal. 101(4): 984-998 (2010) - [j3]Sangyeol Lee, Joseph M. Reinhardt
, Philippe C. Cattin
, Michael D. Abràmoff
:
Objective and expert-independent validation of retinal image registration algorithms by a projective imaging distortion model. Medical Image Anal. 14(4): 539-549 (2010) - [c3]Sangyeol Lee, Michael D. Abràmoff
, Joseph M. Reinhardt
:
Retinal atlas statistics from color fundus images. Medical Imaging: Image Processing 2010: 762310
2000 – 2009
- 2008
- [j2]Koichi Maekawa, Sangyeol Lee
, Takayuki Morimoto
, Ken-ichi Kawai:
Jump diffusion model with application to the Japanese stock market. Math. Comput. Simul. 78(2-3): 223-236 (2008) - [c2]Sangyeol Lee, Michael D. Abràmoff
, Joseph M. Reinhardt
:
Retinal image mosaicing using the radial distortion correction model. Medical Imaging: Image Processing 2008: 691435 - 2007
- [c1]Sangyeol Lee, Michael D. Abràmoff
, Joseph M. Reinhardt
:
Feature-based pairwise retinal image registration by radial distortion correction. Medical Imaging: Image Processing 2007: 651220 - 2006
- [j1]Ji Hwan Cha, Sangyeol Lee
, Jongwoo Jeon:
Sequential Confidence Interval Estimation for System Availability. Qual. Reliab. Eng. Int. 22(2): 165-176 (2006)
Coauthor Index
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