chainladder 0.7.12

Chainladder Package - P&C Loss Reserving package

chainladder - Property and Casualty Loss Reserving in Python

This package gets inpiration 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.

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
DevelopmentConstant	TailConstant	MackChainladder	BerquistSherman
MunichAdjustment	TailBondy	BornhuettterFerguson	Pipeline
ClarkLDF	TailClark	Benktander	GridSearch
IncrementalAdditive		CapeCod	ParallelogramOLF
			Trend

Documentation

Please visit the Documentation page for examples, how-tos, and source code documentation.

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 instal using conda: conda install -c conda-forge chainladder

Alternatively, install directly from github: pip install git+https://github.com/casact/chainladder-python/

Note: This package requires Python 3.5 and later, numpy 1.12.0 and later, pandas 0.23.0 and later, scikit-learn 0.18.0 and later.

Questions?

Feel free to reach out on Gitter.

Want to contribute?

Check out our contributing guidelines.