OGA and HDAIC improve high-dimensional regression with dependent data.
problem High-dimensional linear regression with dependent observations.
method Orthogonal greedy algorithm (OGA) and high-dimensional Akaike's information criterion (HDAIC).
result OGA and HDAIC achieve optimal convergence rate without knowing sparsity.