Univariate Shrinkage in the Cox Model for High Dimensional Data
Univariate Shrinkage in the Cox Model for High Dimensional Data
We propose a method for prediction in Cox's proportional model, when the number of features (regressors), p, exceeds the number of observations, n. The method assumes that the features are independent in each risk set, so that the partial likelihood factors into a product. As such, it is analogous to …