Survival models for insurance — cure models, CLV, lapse tables, MLflow wrapper
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Updated
Apr 4, 2026 - Python
Survival models for insurance — cure models, CLV, lapse tables, MLflow wrapper
Mixture cure models — Weibull/LogNormal/Cox MCM, EM algorithm, Maller-Zhou identifiability, non-claimer scoring
Reproducible R implementation for assessing sufficient follow-up in cure models and applying extreme-value methods when follow-up is insufficient. Includes SFU hypothesis tests, EBVK tail-index estimation, real colon cancer data analysis, curse-of-dimensionality diagnostics, and comparisons with gradient-boosted GP regression.
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