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巨灾模型，基于泊松频率与损失分布模拟巨灾事件并计算超额赔款。适用于精算教学示例与巨灾风险概念演示；基于简化聚合损失计算，不适用于正式巨灾风险定价或再保安排。
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| name | catastrophe-model |
| description | 巨灾模型，基于泊松频率与损失分布模拟巨灾事件并计算超额赔款。适用于精算教学示例与巨灾风险概念演示；基于简化聚合损失计算，不适用于正式巨灾风险定价或再保安排。 |
| version | 1.0.0 |
| author | wangyi |
巨灾模型工具，基于泊松频率与损失分布模拟巨灾事件，计算超额赔款与再保效果。
📌 说明：本工具基于简化模型实现，仅使用 Python 标准库。结果仅供学习参考，不构成投资建议或交易依据。
poisson_sample(lam)泊松分布随机抽样（Knuth算法）。 必填: lam
lognormal_sample(mean, std)对数正态分布抽样。 必填: mean, std
pareto_sample(scale, shape)帕累托分布抽样。 必填: scale, shape
simulate_aggregate_loss(lambda_annual, loss_mean, loss_std, distribution='lognormal', pareto_scale=None, pareto_shape=None, num_simulations=10000)蒙特卡洛模拟年聚合巨灾损失。 必填: lambda_annual, loss_mean, loss_std
catastrophe_excess_of_loss(aggregate_losses, retention, limit)巨灾超赔再保效果分析。 必填: aggregate_losses, retention, limit
percentile(p)python scripts/main.py \
--mean <mean> \
--std <std> \
Based on SOC occupation classification
