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Chainladder Package - P&C Loss Reserving package

Project description

PyPI version Conda Version Build Status codecov io Documentation Status

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-tos, and source code documentation.

Available Estimators

chainladder has an ever growing list of estimators that work seemlessly together:

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        

Installation

To install using pip: pip install chainladder

To instal 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.

Questions or Ideas?

Join in on the github discussions. Your question is more likely to get answered here than on Stack Overflow. We’re always happy to answer any usage questions or hear ideas on how to make chainladder better.

Want to contribute?

Check out our contributing guidelines.

Project details


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Files for chainladder, version 0.8.10
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