A varying-coefficient sequential regression model extends the modified Cholesky decomposition to estimate positive definite covariance matrices as functions of covariates under joint sparsity for high-dimensional responses.
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A covariate-dependent Cholesky decomposition for high-dimensional covariance regression
A varying-coefficient sequential regression model extends the modified Cholesky decomposition to estimate positive definite covariance matrices as functions of covariates under joint sparsity for high-dimensional responses.