Extending the Iterative Convex Minorant Algorithm to the Cox Model for Interval-Censored Data

Abstract The iterative convex minorant (ICM) algorithm proposed by Groeneboom and Wellner is fast in computing the NPMLE of the distribution function for interval censored data without covariates. We reformulate the ICM as a generalized gradient projection method (GGP), which leads to a natural extension to the Cox model. It is also easily extended to support Tibshirani's Lasso method. Some simulation results are also shown. For illustration we reanalyze two real datasets.

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