aggregate Documentation
Introduction
aggregate builds approximations to compound (aggregate) probability distributions quickly and accurately.
It can be used to solve insurance, risk management, and actuarial problems using realistic models that reflect underlying frequency and severity.
It delivers the speed and accuracy of parametric distributions to situations that usually require simulation, making it as easy to work with an aggregate (compound) probability distribution as the lognormal.
aggregate includes an expressive language called DecL to describe aggregate distributions and is implemented in Python under an open source BSD-license.
This help document is in six parts plus a bibliography.
Get up and running: installation, aggregate “hello world”, and a glimpse into the functionality.
How to solve real-world actuarial problems using aggregate.
Documentation for every class and function, for developers and more advanced users.
The Dec Language (DecL) for specifying aggregate distributions.
Probability theory background and the numerical implementation methods employed by aggregate.
Design philosophy, competing products, future development ideas, and historical perspective.