Korea University Department of Statistics

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Professors

교수세부항목
Homepage
Name : Choi, Taeryon (최 태 련)
Position : Professor
TEL : (02) 3290-2245
E-mail : trchoi@korea.ac.kr
Office : 611 CPSE Bldg. 
Research Interests : Bayesian Statistics
Education Ph.D. in Statistics, 2005, Carnegie Mellon University, Pittsburgh, PA, U.S.A.
M.S. in Statistics, 2000, Seoul National University, Seoul, Korea 
B.S. in Computer Science and Statistics, 1998, Seoul National University, Seoul, Korea 
Positions Held

Sep 2015 ~ present, Professor of Statistics, Korea University
Sep 2010 ~ Aug 2015, Associate Professor of Statistics, Korea University
Sep 2009 ~ Aug 2010, Assistant Professor of Statistics, Korea University
Mar 2008 ~ Aug 2009, Assistant Professor of Statistics, Inha University
Aug 2005 ~ Feb 2008, Assistant Professor of Statistics, University of Maryland, Baltimore County 

Books

• Huh, M-H. and Choi, T. (2013). Calculus Essential for Statistics, Kyowoo Co. 
• Shi, J. Q. and Choi, T. (2011) "Gaussian Process Regression Analysis for Functional Data", Chapman & Hall/CRC Press 

Research Papers

International Academic Journals
 

  Lenk, P. J. and Choi, T. (2017). Bayesian analysis of shape-restricted functions using Gaussian process priors. Statistica Sinica, Volume 27, 46-69.

 

• Choi, T. Kim, H-J., and Jo, S. (2016). Bayesian variable selection approach to a Bernstein polynomial regression model with stochastic constraints. Journal of Applied Statistics, Volume 43, 2751-2771.

• Lian, H., Choi, T., Meng, J., and Jo, S. (2016). Posterior convergence for Bayesian functional linear regression.  Journal of Multivariate Analysis, Volume 150, 27-41.

• Yang, J., Zhu, H., Choi, T., and Cox, D. (2016). Smoothing and mean-covariance estimation of functional data with a Bayesian hierarchical model. Bayesian Analysis, Volume 11, 649-670.      
             
• Jo, S., Roh, T. and Choi, T. (2016). Bayesian spectral analysis models for quantile regression with Dirichlet process mixtures.  Journal of Nonparametric Statistics, Volume 28, 177-206. 

• Kim, H-J., Choi, T., and Lee, S. (2016). A hierarchical Bayesian regression model for the uncertain functional  constraint using screened scale mixtures of Gaussian distributions. Statistics : A Journal of Theoretical and Applied Statistics, Volume 50, 350-376.
             
• Hart, J., Choi, T., and Yi, S. (2016). Frequentist nonparametric goodness-of-fit tests via marginal likelihood ratio, Computational Statistics and Data Analysis, Volume 96, 120-132.

• Kim, H-J., Choi, T., and Jo, S. (2016). Bayesian factor analysis with uncertain functional constraints about factor loadings, Journal of Multivariate Analysis, Volume 144, 110-128.

• Choi, T. and Rousseau, J. (2015). A note on Bayes factor consistency in partial linear models, Journal of Statistical Planning and Inference, Volume 166, 158-170.

• Choi, T. and Woo, Y. (2015). A partially linear Model using a Gaussian process prior, Communications in Statistics, Simulation and Computation, Volume 44, Issue 7, 1770-1786.


• Kim, H. and Choi, T. (2014). On Bayesian estimation of regression models subject to uncertainty about functional constraints, Journal of the Korean Statistical Society, Volume 43, Issue 1, 133-147.
    
• Choi, T. and Woo, Y. (2013). On asymptotic properties of Bayesian partially linear models,  Journal of the Korean Statistical Society, Volume 42, Issue 4, 529-541.

• Yi, G., Shi, J. Q. and Choi, T. (2011) "Penalized Gaussian process regression and classification for high-dimensional nonlinear data", Biometrics, Volume 67, Issue 4, 1285-1294.

• Yi, S. and Choi, T. (2011) "A direct approach to understanding posterior consistency of Bayesian regression problems" Communications in Statistics, Theory and Methods, Volume 40, Issue 18, 3316-3326.

• Kim, J.-M., Jung, Y.-S., Choi, T., and Sunger, E. A. (2011) "Partial correlation with Copula modeling" Computational Statistics and Data Analysis, Volume 55, Issue 3, 1357-1366.

• Kim, J-M, Sungur, E. A., Choi, T., and Heo, T.-Y. (2011) "Generalized Bivariate Copulas and Their Properties", Model Assisted Statistics and Applications-International Journal; Vol. 6, 127-136.

• Choi, T., Shi, J. Q., and Wang, B. (2011) "A Gaussian process regression approach to a single-index model", Journal of Nonparametric Statistics, vol.23, No. 1, 21-36.

• Choi, T., Schervish, M. J., Schmitt, A. K., and Small, M. J. (2010) "Bayesian Hierarchical Analysis for Multiple Health Endpoints in a Toxicity Study", Journal of Agricultural, Biological and Environmental Statistics, vol. 15, No. 3, 290-307.

• Choi, T. (2009) "Asymptotic properties of posterior distributions in nonparametric regression with non-Gaussian errors", Annals of the Institute of Statistical Mathematics, vol. 61, No. 4, pp 835-859.

• Choi, T., Lee, J., and Roy, A. (2009), "A note on the Bayes factor in a semiparametric regression model", Journal of Multivariate Analysis, vol. 100, Issue 6, pp 1316-1327.

• Choi, T. (2008) "Convergence of posterior distribution in the mixture of regressions", Journal of Nonparametric Statistics, vol. 20, Issue 4, pp 337-351.

• Choi, T. and Ramamoorthi, R. V. (2008) "Remarks on consistency of posterior distributions", IMS Collections, vol. 3, Pushing the Limits of Contemporary Statistics : Contributions in Honor of Jayanta K. Ghosh, pp 170-186.

• Choi, T., Schervish, M. J., Schmitt, A. K., and Small, M. J. (2008) "A Bayesian approach to logistic regression model with incomplete information", Biometrics, vol. 64, Issue 2, pp 424-430.

• Choi, T., Schervish, M. J. (2007) "On posterior consistency in nonparametric problems", Journal of Multivariate Analysis, vol. 98, Issue 10, pp 1969-1987.

• Choi, T. (2007) "Alternative posterior consistency results in nonparametric binary regression using Gaussian process priors", Journal of Statistical Planning and Inference, vol. 137, 2979-2983.

• Choi, K., Kim, D., and Choi, T. (2006) "Estimating the number of clusters using a multivariate location test statistics", Springer Lecture note in Computer Science (LNCS-LNAI 4223), Fuzzy Systems and Knowledge Discovery, 373-382.

Domestic Academic Journals

 

 Jo, S., Seok, I. and Choi, T. (2016). A nonparametric Bayesian seemingly unrelated regression model, The Korean Journal of Applied Statistics, 29(4), 627-641.

 

 Roh, T. and Choi, T. (2016). A comparison study of Bayesian shrinkage methods for vector autoregressive models, Journal of the Korean Data Analysis Society, 18(4), 1857-1870.

 

 Kim, H., Jo, S. and Choi, T. (2015). Performance comparison of random number generators based on adaptive rejection sampling, Journal of the Korean Data & Information Science Society, 26(3), 593-610.

 

 Cho, M., Choi, T. and Lee, R. (2014). Empirical analysis of Bayesian stochastic volatility models with leverage effect, Journal of the Korean Data Analysis Society, 16(2), 703-717.

 

• Lee, M., Choi, T., Kim, J. and Woo, H. (2013). Bayesian analysis of dose-effect relationship of Cadmium for benchmark dose evaluation, The Korean Journal of Applied Statistics, 26(3), 453-470.

 

 Oh, Y., Choi, T. and Cho, M. (2012). Empirical study on Bayesian model selection of stochastic volatility models using deviance information criterion, Journal of the Korean Data Analysis Society, 14(4), 1871-1888.

 

 Woo, Y., Choi, T, and Kim W. (2012). A comparison study on the performance of Bayesian partially linear models, Korean Communications in Statistics, 19(6), 885-898.

 

 Lee, J., Choi, T., and Woo, Y. (2011) "Bayesian approaches to zero inflated Poisson model", The Korean journal of applied statistics, 24(4), 677-693.

 

 Choi, T. (2010) "Estimating a benchmark dose in dose response studies via Bayesian hierarchical methods", Journal of the Korean Data Analysis Society, Vol. 12, No.1, pp119-133