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Author:
Elí Gaiska Salomón-Guzmán
Summary:
Peaks-over-threshold GPD tail inference with continuous and interval-censored (grouped) fits, profile-likelihood intervals for shape, endpoint and return levels, grouped scale regression, permutation trend tests, power/MDE, a sequential Monte Carlo precision protocol, finite-sample calibration, and multi-source robustness.
Latest version:
1.2.2
Required dependencies:
numpy
|
scipy
Optional dependencies:
build
|
matplotlib
|
mypy
|
pandas
|
pytest
|
pytest-cov
|
ruff
|
streamlit
|
twine
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