A novel moment-based sufficient dimension reduction approach in multivariate regression. - Jae Keun Yoo (Comput. Stat. Data Anal., 2008)

Response dimension reduction for the conditional mean in multivariate regression. - Jae Keun Yoo; R. Dennis Cook (Comput. Stat. Data Anal., 2008)

On the extension of sliced average variance estimation to multivariate regression. - Jae Keun Yoo; Keunbaik Lee; Seongho Wu (Stat. Methods Appl., 2010)

Modeling the random effects covariance matrix for generalized linear mixed models. - Keunbaik Lee; Jung Bok Lee; Joseph Hagan; Jae Keun Yoo (Comput. Stat. Data Anal., 2012)

Advances in seeded dimension reduction: Bootstrap criteria and extensions. - Jae Keun Yoo (Comput. Stat. Data Anal., 2013)

Bayesian Cholesky factor models in random effects covariance matrix for generalized linear mixed models. - Keunbaik Lee; Jae Keun Yoo (Comput. Stat. Data Anal., 2014)

Dimension test approach of heteroscedasticity in the linear model. - Keunbaik Lee; Hyejin Song; Jae Keun Yoo (Commun. Stat. Simul. Comput., 2017)

Do we need the constant term in the heterogenous autoregressive model for forecasting realized volatilities? - Hyejin Song; Dong Wan Shin; Jae Keun Yoo (Commun. Stat. Simul. Comput., 2018)

Basis-Adaptive Selection Algorithm in dr-package. - Jae Keun Yoo (R J., 2018)

On cross-distance selection algorithm for hybrid sufficient dimension reduction. - Yujin Park; Kyongwon Kim; Jae Keun Yoo (Comput. Stat. Data Anal., 2022)

On a nonlinear extension of the principal fitted component model. - Jun Song; Kyongwon Kim; Jae Keun Yoo (Comput. Stat. Data Anal., 2023)

Nonlinear Functional Sufficient Dimension Reduction via Principal Fitted Components. - Minjee Kim; Yujin Park; Kyongwon Kim; Jae Keun Yoo (Stat. Comput., 2025)

On sufficient dimension reduction methods based on a graphical model with non-concave penalty. - Yujin Park; Kyongwon Kim; Jae Keun Yoo (Stat. Comput., 2025)