Python Package - ChainLadder¶
Source: casact/chainladder-python: Actuarial reserving in Python
Docs: Welcome to Chainladder — Reserving in Python
chainladder - Property and Casualty Loss Reserving in Python¶
This package gets inspiration from the popular R ChainLadder package.
This package strives to be minimalistic in needing its own API. Think in pandas for data manipulation and scikit-learn for model construction.
An actuary already versed in these tools will pick up this package with ease. Save your mental energy for actuarial work.
Documentation¶
Please visit the Documentation page for examples, how-to’s, and source code documentation.
Available Estimators¶
| Loss Development | Tails Factors | IBNR Models | Adjustments | Workflow |
|---|---|---|---|---|
| Development | TailCurve | Chainladder | BootstrapODPSample | VotingChainladder |
| DevelopmentConstant | TailConstant | MackChainladder | BerquistSherman | Pipeline |
| MunichAdjustment | TailBondy | BornhuettterFerguson | ParallelogramOLF | GridSearch |
| ClarkLDF | TailClark | Benktander | Trend | |
| IncrementalAdditive | CapeCod | |||
| CaseOutstanding | ||||
| TweedieGLM | ||||
| DevelopmentML | ||||
| BarnettZehnwirth |
Getting Started Tutorials¶
Tutorial notebooks are available for download here.
- Working with Triangles
- Selecting Development Patterns
- Extending Development Patterns with Tails
- Applying Deterministic Methods
- Applying Stochastic Methods
- Large Datasets
Installation¶
To install using pip: pip install chainladder
To install using conda: conda install -c conda-forge chainladder
Alternatively for pre-release functionality, install directly from github: pip install git+https://github.com/casact/chainladder-python/
Note: This package requires Python>=3.5 pandas 0.23.0 and later, sparse 0.9 and later, scikit-learn 0.23.0 and later.
Related¶
- Development
- R Package - ChainLadder
- 2-Areas/MOCs/Python
- Actuarial Science
- CAS - Casualty Actuarial Society
Backlinks:
list from [[Python Package - ChainLadder]] AND -"Changelog"