Copula-Robust Cramér–Rao Lower Bound underDependent Random Censoring

In survival analysis and reliability theory, the classical Cramér–Rao lower bound assumes independence between lifetime and censoring variables. This paper extends the bound to dependent censoring using a copula-based likelihood. We derive a robust Godambe information bound and prove a generalized Cramér–Rao inequality. The result reduces to the classical bound under independence and shows increased variance bounds with stronger dependence.

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