오만숙(吳滿淑) 교수
통계학과
- 종합과학관 B동 B512호
- 02-3277-2374
- 면담 가능시간
- 월 3-4 수 2-4
연구실적
- An Interactive Online App for Predicting Diabetes via Machine Learning from Environment-Polluting Chemical Exposure Data International Journal of Environmental Research and Public Health, 2022, v.19 no.10, 5800
- Regional source apportionment of PM2.5 in Seoul using Bayesian multivariate receptor model Journal of Applied Statistics, 2022, v.49 no.3, 738-751
- Bayesian analysis of multivariate crash counts using copulas ACCIDENT ANALYSIS AND PREVENTION, 2021 , 105431
- Bayesian multivariate receptor modeling software: BNFA and bayesMRM Chemometrics and Intelligent Laboratory Systems, 2021, v.211, 104280
- 베이지안 분위회귀모형을 이용한 지역인구에 영향을 미치는 요인분석 응용통계연구, 2021, v.34 no.5, 823-835
- Serum biomarkers from cell-based assays for AhRL and MIS strongly predicted the future development of diabetes in a large community-based prospective study in Korea Scientific Reports, 2020, v.10 no.1, 6339
- Accounting for uncertainty in source-specific exposures in the evaluation of health effects of pollution sources on daily cause-specific mortality ENVIRONMETRICS, 2018, v.29 no.1
- Bayesian analysis of financial volatilities addressing long-memory, conditional heteroscedasticity and skewed error distribution Communications for Statistical Applications and Methods, 2017, v.24 no.5, 507-518
- 영과잉 토빗모형을 이용한 한국 소득분포 자료의 베이지안 분석 응용통계연구, 2017, v.30 no.6, 917~929
- Bayesian quantile multivariate receptor modeling Chemometrics and Intelligent Laboratory Systems, 2016, v.159, 174-180
- Bayesian variable selection in binary quantile regression Statistics and Probability Letters, 2016, v.118, 177-181
- Bayesian variable selection in quantile regression using the Savage-Dickey density ratio Journal of the Korean Statistical Society, 2016, v.45 no.3, 466-476
- Volatility spillover between the Korean KOSPI and the Hong Kong HSI stock markets Communications for Statistical Applications and Methods, 2016, v.23 no.3, 203~213
- Robust Bayesian multivariate receptor modeling Chemometrics and Intelligent Laboratory Systems, 2015, 2 SEP 2015
- Assessment of source-specific health effects associated with an unknown number of major sources of multiple air pollutants: a unified Bayesian approach BIOSTATISTICS, 2014, v.15 no.3, 484-497
- Bayesian comparison of models with inequality and equality constraints STATISTICS & PROBABILITY LETTERS, 2014, v.84, 176-182
- Bayesian test on equality of score parameters in the order restricted RC association model COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2014, v.72, 147-157
- 부등 제한 조건하에서의 베이지안 추론 응용통계연구, 2014, 제27권 6호, 909-922
- [학술지논문] Prediction of PM10 concentration in Seoul, Korea using Bayesian network Communications for Statistical Applications and Methods, 2023, v.30 no.5 , 517-530
- [학술지논문] An Interactive Online App for Predicting Diabetes via Machine Learning from Environment-Polluting Chemical Exposure Data INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, v.19 no.10 , 5800-5800
- [학술지논문] BayMDS: An R Package for Bayesian Multidimensional Scaling and Choice of Dimension APPLIED PSYCHOLOGICAL MEASUREMENT, 2022, v.46 no.3 , 250-251
- [학술지논문] Regional source apportionment of PM2.5 in Seoul using Bayesian multivariate receptor model JOURNAL OF APPLIED STATISTICS, 2022, v.49 no.3 , 738-751
- [학술지논문] Bayesian analysis of multivariate crash counts using copulas ACCIDENT ANALYSIS AND PREVENTION, 2021, v.149 no.0 , 105431-105431
- [학술지논문] Bayesian multivariate receptor modeling software: BNFA and bayesMRM CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2021, v.211 no.0 , 104280-104280
- [학술지논문] 베이지안 분위회귀모형을 이용한 지역인구에 영향을 미치는 요인분석 응용통계연구, 2021, v.34 no.5 , 823-835
- [학술지논문] Serum biomarkers from cell-based assays for AhRL and MIS strongly predicted the future development of diabetes in a large community-based prospective study in Korea SCIENTIFIC REPORTS, 2020, v.10 no.1 , 6339-6339
- [저역서] 기초통계학 경문사, 2023, 281
- [저역서] JAGS를 활용한 베이지안 자료분석 자유아카데미, 2019, 231
- [학술발표] Bayesian Quantile Multivariate Receptor Modeling 2021 Joint Statistical Meeting , 미국, Seattle, 2021-08-11 Proceedings of 2021 JSM, 2021
- [학술발표] Application of a Bayesian multivariate receptor model to identify major PM2.5 source areas in Seoul 한국통계학회 2019 춘계학술논문발표회, 대한민국, 춘천, 2019-05-24 한국통계학회 2019 춘계학술논문발표회 프로시딩, 2019, 76-76
- [학술발표] Modeling the multivariate conjugate prior based on copula method 한국통계학회 2019 춘계학술논문발표회, 대한민국, 춘천, 2019-05-24 한국통계학회 2019 춘계학술논문발표회 프로시딩, 2019, 64-64
- [학술발표] Practical MCMC for Bayesian analysis of air pollution data Extreme value analysis 2019, 크로아티아, 자그레브, 2019-07-02 Book of Abstracts EVA 2019, 2019, 127-127
- [학술발표] Predicting the progression of diabetes via machine learning 한국통계학회 2019 춘계학술논문발표회, 대한민국, 춘천, 2019-05-24 한국통계학회 2019 춘계학술논문발표회 프로시딩, 2019, 72-72
강의
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2024-1학기
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확률및통계학 강의 계획서 상세보기
- 학수번호 34980분반 01
- 1학년 ( 3학점 , 3시간) 월 6~6 (종A) , 수 5~5 (102)
- 수강불가->통계학Ⅰ, 응용통계입문 이전/현재 수강자
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베이지안통계특론 강의 계획서 상세보기
- 학수번호 G11830분반 01
- 학년 ( 3학점 , 3시간) 수 2~3 (종D106)
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2023-2학기
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확률및통계학 강의 계획서 상세보기
- 학수번호 34980분반 01
- 1학년 ( 3학점 , 3시간) 월 6~6 (포363) , 수 5~5 (포363)
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베이지안통계 강의 계획서 상세보기
- 학수번호 G11876분반 01
- 학년 ( 3학점 , 3시간) 수 2~3 (종D106)
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2023-1학기
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확률및통계학 강의 계획서 상세보기
- 학수번호 34980분반 01
- 1학년 ( 3학점 , 3시간) 월 6~6 (종A) , 수 5~5 (102)
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베이지안통계특론Ⅰ 강의 계획서 상세보기
- 학수번호 G11830분반 01
- 학년 ( 3학점 , 3시간) 수 2~3 (종D109)
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2022-2학기
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확률및통계학
- 학수번호 34980분반 01
- 1학년 ( 3학점 , 3시간)
- 원격강의
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베이지안통계
- 학수번호 G11876분반 01
- 학년 ( 3학점 , 3시간) 수 3~4 (종D106)
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2021-2학기
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확률및통계학
- 학수번호 34980분반 01
- 1학년 ( 3학점 , 3시간) 월 5~5 , 수 4~4
- 원격강의
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베이지안통계
- 학수번호 G11876분반 01
- 학년 ( 3학점 , 3시간) 월 6~7 (종D109)
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-
2021-1학기
-
확률및통계학
- 학수번호 34980분반 01
- 1학년 ( 3학점 , 3시간) 월 6~6 , 수 5~5
- 원격강의
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베이지안통계특론Ⅰ
- 학수번호 G11830분반 01
- 학년 ( 3학점 , 3시간) 수 3~4
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학력
Purdue University Ph.D.(통계학)