Dependence-aware block-maxima inference

Severity, persistence, and design-life levels under serial dependence.

UniBM is a Python package for dependence-aware block-maxima inference in heavy-tailed time series. It keeps severity inference, persistence inference, and design-life levels in one coherent workflow while exposing a small public API under unibm, unibm.evi, unibm.ei, and unibm.cdf.

Compare estimation error, interval score, and coverage against known targets in the EVI and EI benchmark.

This site is package-first. Case figures and benchmark summaries are frozen outputs: the browser renders them but never downloads data or fits a model. Repository-level orchestration remains in the root README and justfile.