Ultrahigh dimensions

Monday, September 16, 2019 - 2:30pm - 3:30pm
Runze Li (The Pennsylvania State University)
We develop a new estimation and valid inference method for low-dimensional regression coefficients in high-dimensional generalized linear models. The proposed estimator is computed by solving a score function. We recursively conduct model selection to reduce the dimensionality from high to a moderate scale and construct the score equation based on the selected variables. The proposed confidence interval (CI) achieves valid coverage without assuming consistency of the model selection
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