# aggregate Documentation

**aggregate** is a Python package providing fast, accurate, and expressive data
structures that make working with aggregate (also called compound) probability distributions
easy and intuitive. It allows students and practitioners to work with realistic
real-world distributions that reflect the underlying frequency and severity
generating processes. It has applications in insurance, risk management, actuarial
science, and related areas.

## Table of Contents

- aggregate Quick Start
- 1. Tutorials
- 2. How-To Guides
`aggregate`

: Basic Examples- Create a simple aggregate distribution, plot and statistics
- Portfolio Examples
- Script Examples
- More complex program
- Integrated Parser
- Distortions and Pricing
- Another Interesting Example
- Distortions
- The plot of EXEQA is very intesting… different behaviours at different size losses
- Credit Puzzle and Empirical Distortions
- Working with Meta objects

- 3. Discussion
- Main Features
- Potential Applications
- Practical Modeling Examples
- Missing Features
- History
- Reinsurance Pricing Applications
- Insurance Pricing Applications
- Capital Modeling
- Capital Allocation and Pricing
- Design and Build
- Non programming Enhancements
- Short term
- Medium Term
- Nice to have enhancements
- The Underwriter

- 4. Reference
- 5.
**agg**Language Reference - 6. Technical Resources

Other things to find,

```
/s/telos/python/examples/snippets/discrete_aggregates.ipynb
/s/telos/python/examples/snippets/dice_aggregates.ipynb
/s/telos/python/examples/snippets/mixed_exponentials.ipynb
/s/telos/python/examples/snippets/Tweedie.ipynb
/s/telos/python/examples/snippets/basic_reinsurance.ipynb
/s/telos/python/examples/snippets/limit_profiles_mixed_severity_mixing.ipynb
```