lossmodels

Severity and frequency fitting and aggregate loss distributions.

Overview

lossmodels covers the loss-distribution workflow from data to aggregate: a severity catalog spanning the classic distributions and the transformed beta and transformed gamma families, frequency models, maximum likelihood that is truncation- and censoring-aware, fit diagnostics and model selection, and aggregate distributions via simulation, FFT, and Panjer recursion.

Every severity model shares one interface — moments, quantiles, limited expected values, increased-limits tables — so fitted models drop directly into coverage modifications, aggregates, and the wider ecosystem.

Installation

pip install lossmodels

Requires Python 3.10 or newer.

Quick start

from lossmodels import Poisson, Lognormal, CollectiveRiskModel

freq = Poisson(lam=2.0)
sev = Lognormal(mu=10.0, sigma=0.8)
model = CollectiveRiskModel(freq, sev)

print("Mean     :", model.mean())
print("Variance :", model.variance())
print("VaR 95%  :", model.var(0.95))
print("TVaR 95% :", model.tvar(0.95))

samples = model.sample(50_000, rng=0)
print("Simulated mean:", samples.mean())

What's inside

• Severity — classic and extended catalogs (including the transformed beta and transformed gamma families) behind one shared interface, plus increased-limits and loss-elimination tables.
• Frequency — Poisson, negative binomial, and related counting models.
• Estimation — MLE with truncation and censoring support, parameter uncertainty, goodness-of-fit diagnostics, and model comparison.
• Aggregate — CollectiveRiskModel simulation, FFT and Panjer recursion, stop-loss and risk measures.
• Coverage — deductibles, limits, and coinsurance applied analytically.
• Empirical — nonparametric counterparts for validation.

The full API reference and end-to-end worked examples live at openactuarial.org/lossmodels.html.

The OpenActuarial ecosystem

lossmodels is one of seven packages that share conventions — tidy tables, explicit distribution parameterizations, reproducible random-number handling — and compose across package seams:

Install everything at once with pip install openactuarial.

Development

git clone https://github.com/OpenActuarial/lossmodels
cd lossmodels
python -m pip install -e ".[dev]"
pytest
ruff check src tests

CI runs the same gate on Python 3.10–3.14 across Linux and Windows.

Versioning and stability

All ecosystem packages are pre-1.0: minor releases may change APIs, and every release is documented in CHANGELOG.md. Current per-package API stability is tracked at openactuarial.org/stability.html.

License

MIT — see LICENSE.