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Faculty - Statistics

  • Professor Mixture model
  • SEO, BYUNG TAE

Research Interest

 Mixture models, Nonparametric density estimation, Minimum distance estimation

Education

  • (Ph.D.) Pennsylvania State University
  • (B.S.) Seoul National University

Experience

  • Assistant professor at Texas Tech University
  • Professor at Sungkyunkwan University

Journal Articles

  • (2023)  Merging Components in Linear Gaussian Cluster-Weighted Models.  JOURNAL OF CLASSIFICATION.  40,  1
  • (2023)  Accelerated failure time modeling via nonparametric mixtures.  BIOMETRICS.  79,  1
  • (2022)  Penalized maximum likelihood estimation with symmetric log-concave errors and LASSO penalty.  Communications for Statistical Applications and Methods.  29,  6
  • (2022)  Density deconvolution under a k-monotonicity constraint.  STATISTICS AND COMPUTING.  32,  5
  • (2021)  Omnibus goodness of fit test based on quadratic distance.  JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION.  91,  18
  • (2021)  Semiparametric estimation for nonparametric frailty models using nonparametric maximum likelihood approach.  STATISTICAL METHODS IN MEDICAL RESEARCH.  30,  11
  • (2021)  Modal linear regression using log-concave distributions.  JOURNAL OF THE KOREAN STATISTICAL SOCIETY.  50,  2
  • (2020)  Semiparametric estimation for linear regression with symmetric errors.  COMPUTATIONAL STATISTICS & DATA ANALYSIS.  152,  1
  • (2018)  Linear regression under log-concave and Gaussian scale mixture errors: comparative study.  Communications for Statistical Applications and Methods.  25,  6
  • (2017)  The doubly smoothed maximum likelihood estimation for location-shifted semiparametric mixtures.  COMPUTATIONAL STATISTICS & DATA ANALYSIS.  108,  1
  • (2017)  Adaptive robust regression with continuous Gaussian scale mixture errors.  JOURNAL OF THE KOREAN STATISTICAL SOCIETY.  46,  1
  • (2016)  Semiparametric mixture: Continuous scale mixture approach.  COMPUTATIONAL STATISTICS & DATA ANALYSIS.  103,  1
  • (2016)  Semiparametric maximum likelihood estimation of stochastic frontier model with errors-in-variables.  JOURNAL OF THE KOREAN STATISTICAL SOCIETY.  45,  2
  • (2015)  Family strategy of economic inequality among brothers in Korean rural society, 1690-1795.  HISTORY OF THE FAMILY.  20,  2
  • (2015)  A new algorithm for maximum likelihood estimation in normal scale-mixture generalized autoregressive conditional heteroskedastic models.  JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION.  85,  1
  • (2014)  Assessment of the number of components in Gaussian mixture models in the presence of multiple local maximizers.  JOURNAL OF MULTIVARIATE ANALYSIS.  125,  3
  • (2013)  Nearly universal consistency of maximum likelihood in discrete models.  STATISTICS & PROBABILITY LETTERS.  83,  7
  • (2013)  A universally consistent modification of maximum likelihood.  STATISTICA SINICA.  23,  2
  • (2012)  Root selection in normal mixture models.  COMPUTATIONAL STATISTICS & DATA ANALYSIS.  56,  8
  • (2012)  A Fast EM Algorithm for Gaussian Mixtures.  Communications for Statistical Applications and Methods.  19,  1

Honors / Awards

  • KOFST 23rd Research Award, Korean Federation of Science and Technology Societies, 2013
  • SKKU Teaching Award, Sungkyunkwan University, 2013
  • Research Promotion Award, Korean Statistical Society, 2017

Conference Paper

  • (2022)  Accelerated failure time modelling via nonparametric mixtures.  5th International Conference on Econometrics and Statistics.  JAPAN
  • (2021)  A semiparametric AFT random-effect model.  4th International Conference on Econometrics and Statistics.  HONG KONG
  • (2019)  Accelerated failure time model based on nonparametric Gaussian scale mixtures.  12th International Conference of the Computational and Methodological Statistics.  UNITED KINGDOM
  • (2019)  Efficient and robust estimation of regression parameters.  2019년도 한국 통계학회 춘계 학술논문 발표회.  KOREA, REPUBLIC OF
  • (2018)  Robust regression with Gaussian scale mixture errors.  Advances in finite mixture and ohter non-regular models.  CHINA
  • (2018)  Doubly smoothed MLE in location-shifted semiparametric mixtures.  The 27th South Taiwan Statistics Conference.  TAIWAN
  • (2018)  Doubly smoothed maximum likelihood estimation iwth application to semiparametric structural measurement error models.  2nd International Conference on Econometrics and Statistics.  HONG KONG
  • (2017)  Doubly Smoothed MLE in Semiparametric Mixtures.  2017 Joint Statistical Meetings.  UNITED STATES
  • (2017)  Accelerated Failure Time Model with Log-Concave Error Distribution.  2017 Joint Statistical Meetings.  UNITED STATES
  • (2016)  Stochastic frontier models with errors-in-variables.  2016년도 한국통계학회 춘계 학술논문발표회 프로시딩.  KOREA, REPUBLIC OF
  • (2015)  Semiparametric maximum likelihood estimation of stochastic frontier model with errors-in-variables.  2015 추계 한국통계학회.  KOREA, REPUBLIC OF
  • (2014)  Finite mixtures with nonparametric symmetric component densities.  2014 추계 한국통계학.  KOREA, REPUBLIC OF
  • (2014)  On singular and spurious solutions in finite mixture models.  21st Internal Conference on Computational Statistics.  SWITZERLAND
  • (2014)  A new ECM algorithm for finite mixtures.  2014 춘계 한국통계학회.  KOREA, REPUBLIC OF
  • (2013)  Unstricted MLE for semiparametric models with missing covariates.  2013 추계한국통계학회.  KOREA, REPUBLIC OF
  • (2012)  Adaptive robust regression with infinite Gaussian scale mixture errors.  추계한국통계학회.  KOREA, REPUBLIC OF
  • (2012)  Estimated Quasi-maximum likelihood estimator for GARCH models based on non-parametric MLE.  The 2nd institute of mathematical statistics Asia pacific rim meeting.  JAPAN
  • (2012)  Root selection in normal mixture models.  춘계 한국 통계학회.  KOREA, REPUBLIC OF
  • (2011)  A latent class selection model for missing data.  2011년도 추계 학술논문발표회 프로시딩.  KOREA, REPUBLIC OF