(2023)
프로빗 모형을 이용한 2016 가계금융복지조사 자료분석.
한국데이터정보과학회지.
34,
3
(2023)
경시적 자료에서 공분산 행렬의 모형화 방법 비교 연구.
한국데이터정보과학회지.
34,
2
(2023)
A Bayesian method for multinomial probit model.
JOURNAL OF THE KOREAN STATISTICAL SOCIETY.
52,
1
(2022)
베이지안 다변량 선형 모형을 이용한 청소년 패널 데이터 분석.
응용통계연구.
35,
6
(2022)
Robust probit linear mixed models for longitudinal binary data.
BIOMETRICAL JOURNAL.
64,
7
(2022)
강건한 프로빗 선형 혼합모형을 이용한 고령화연구패널조사 자료 분석.
한국데이터정보과학회지.
33,
4
(2022)
Robust modeling of multivariate longitudinal data using modified Cholesky and hypersphere decompositions.
COMPUTATIONAL STATISTICS & DATA ANALYSIS.
170,
(2022)
베이지안 다변량 선형모형의 비교 연구.
한국데이터정보과학회지.
33,
2
(2022)
다변량 t-선형모형을 이용한 조세재정 패널데이터 분석.
한국데이터정보과학회지.
33,
1
(2021)
Analysis of multivariate longitudinal data using ARMA Cholesky and hypersphere decompositions.
COMPUTATIONAL STATISTICS & DATA ANALYSIS.
156,
(2021)
Determination of correlations in multivariate longitudinal data with modified Cholesky and hypersphere decomposition using Bayesian variable selection approach.
STATISTICS IN MEDICINE.
40,
4
(2020)
다변량 선형모형을 이용한 노동패널자료 분석.
한국데이터정보과학회지.
31,
4
(2020)
다변량 경시적 자료 분석을 위한 공분산 행렬의 모형화 비교 연구.
응용통계연구.
33,
3
(2020)
Bayesian baseline-category logit random effects models for longitudinal nominal data.
Communications for Statistical Applications and Methods.
27,
2
(2020)
Bayesian cumulative logit random effects models with ARMA random effects covariance matrix.
JOURNAL OF THE KOREAN STATISTICAL SOCIETY.
49,
1
(2020)
Estimation of covariance matrix of multivariate longitudinal data using modified Choleksky and hypersphere decompositions.
BIOMETRICS.
76,
1
(2019)
On fused dimension reduction in multivariate regression.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS.
193,
Publications
(2022)
경시적 자료분석 R활용.
자유아카데미.
Solo
(2021)
스토리가 있는 통계학 (번역본).
(주)신한출판미디어.
Lead author
Conference Paper
(2023)
Analysis of Multivariate Longitudinal Binary Data Using Multivariate Probit Linear Mixed Models.
한국데이터정보과학회 2023년 추계 학술발표회.
KOREA, REPUBLIC OF
(2023)
Multivariate Probit Linear Mixed Models for Multivariate Longitudinal Binary Data.
The 2023 International Conference for Statistical and Data.
TAIWAN
(2023)
Robust modeling of long series of multivariate longitudinal data.
한국데이터정보과학회 2023년 춘계 학술발표회.
KOREA, REPUBLIC OF
(2022)
Bayesian cumulative probit linear mixed models for longitudinal ordinary data.
DSSV 2022: Data Science, Statistics & Visualisation.
TAIWAN
(2021)
Analysis of Longitudinal Binary Data using Probit Linear Mixed Models.
한국데이터정보과학회 2021년 추계 학술발표회.
KOREA, REPUBLIC OF
(2021)
Robust probit linear mixed models for longitudinal binary data.
한국통계학회 창립50주년기념 추계학술논문발표회.
KOREA, REPUBLIC OF
(2021)
Robust modeling of multivariate longitudinal data using modified Cholesky and hypersphere decompositions.
Data Science, Statistics & Visualisation 2021 (online conference).
NETHERLANDS
(2021)
Robust estimation for multivariate t linear mixed models for multivariate longitudinal data.
한국데이터정보과학회 2021년 춘계 학술발표회.
KOREA, REPUBLIC OF
(2020)
Determination of correlations in multivariate longitudinal data analysis using Bayesian variable selection approach.
2020년도 한국통계학회 춘계학술논문발표회.
KOREA, REPUBLIC OF
(2019)
Analysis of Longitudinal Data from Clinical Trials: Review.
2019년 임상시험 및 연구를 위한 산관학 공동 통계 컨퍼런스.
KOREA, REPUBLIC OF
(2019)
Analysis of longitudinal binary and survival time data using joint models with general random effects covariance matrix.
EAC-ISBA 2019.
JAPAN
(2019)
Bayesian joint models for longitudinal binary and survival data using general random effects covariance matrix.
EcoSta 2019.
TAIWAN
(2018)
Modeling of covariance matrix in linear models for multivariate longitudinal data.
2018 한국데이터정보과학회 추계학술발표회.
KOREA, REPUBLIC OF
(2018)
Multivariate linear models for multivairate longitudinal data.
Statistical Computing Challenges and Opportunities in Data Science.
CHINA
(2018)
Bayesian baseline-category logit random effects models with general random effects covariance matrix.
2018년도 한국통계학회 추계 학술논문발표회.
KOREA, REPUBLIC OF
(2018)
Bayesian modeling of random effects covariance matrix in baseline-logit random effects models.
Japanese Joint Statistical Meeting 2018.
JAPAN
(2018)
Bayesian cumulative logit random effects models for longitudinal ordinal data.
EcoSta 2018.
HONG KONG
(2018)
Marginalized random effects models with ARMA random effects covariance matrix.
2018년도 한국통계학회 춘계학술논문발표회.
KOREA, REPUBLIC OF
(2017)
Modeling the ARMA random effects covariance matrix in logistic random effects models.
CFE-CMStatistics 2017.
UNITED KINGDOM
(2017)
Analysis of longitudinal binary data using ARMA Cholesky decomposition.
2017 International Statistical Symposium CSA-KSS-JSS Special Invited Sessions.
TAIWAN