One consistency theorem for coarsened-data maximum likelihood: a cross-domain synthesis of the coarsening-at-random framework

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1. 1Identifiability under imperfect coarsening: sensitivity bounds and the singleton sample complexity that restores them2026
2. 2Identifiability under imperfect coarsening: sensitivity bounds and the singleton sample complexity that restores them2026 · 2 citations
3. 3Coarsening at Random: A Small Monograph on Masked-Data Identifiability Across Domains2026
4. 4Dimensional Asymptotics of Euler-Based Simulated Likelihood for Multidimensional Diffusions2026
5. 5Coarsening at random for differential privacy: analyst-side identifiability under privacy mechanisms2026