Semisupervised Inference for Explained Variance in High Dimensional Linear Regression and its Applications
Semisupervised Inference for Explained Variance in High Dimensional Linear Regression and its Applications
Summary The paper considers statistical inference for the explained variance βTΣβ under the high dimensional linear model Y = Xβ + ε in the semisupervised setting, where β is the regression vector and Σ is the design covariance matrix. A calibrated estimator, which efficiently integrates both labelled and unlabelled data, …