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Regularization for Variable Selection with Flexible Missingness Mechanism: Methodology, Algorithm and Application
(State University of New York at Buffalo, 2018)
Regularized likelihood has been proven to be effective in variable selection. This method has been well developed theoretically and computationally in the past two decades. However, two major problems still exist in practice. ...