4 papers
A covariate-dependent Cholesky decomposition for high-dimensional covariance regression
Rakheon Kim, Emma Jingfei Zhang
Estimation of covariance matrices is a fundamental problem in multivariate statistics. Recently, growing efforts have focused on incorporating covariate effects into these matrices…
Subspace Ordering for Maximum Response Preservation in Sufficient Dimension Reduction
Derik T. Boonstra, Rakheon Kim, Dean M. Young
Sufficient dimension reduction (SDR) methods aim to identify a dimension reduction subspace (DRS) that preserves all the information about the conditional distribution of a respons…
Precision Matrix Regularization in Sufficient Dimension Reduction for Improved Quadratic Discriminant Classification
Derik T. Boonstra, Rakheon Kim, Dean M. Young
Sufficient dimension reduction (SDR) methods, which often rely on class precision matrices, are widely used in supervised statistical classification problems. However, when class-s…
A Sparse Linear Model for Positive Definite Estimation of Covariance Matrices
Rakheon Kim, Irina Gaynanova
Sparse covariance matrices play crucial roles by encoding the interdependencies between variables in numerous fields such as genetics and neuroscience. Despite substantial studies…