Korea University Department of Statistics

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 

• 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 

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