Functional-Based Chain Ladder for Claims Reserving
S3 Method Class profileLadder
Exploration of Run-Off Triangle Increments
Access Markov Chain Breaks for Run-Off Triangle Increments
MACRAME Based Development Profile Reserve
Access Markov Chain States in the MACRAME Algorithm
Access Markov Chain Transition Matrix in the MACRAME Algorithm
Observed Run-Off Triangle Layout vs. Predicted (Unknown) Layout
Parallel Based Development Profile Reserve
Permutation Bootstrap Reserve (PARALLAX, REACT, MACRAME)
Visualization of the Run-Off Triangle Increments for the Markov Chain
Plotting the Output of the Permutation Bootstrap
Plotting Development Profiles
Plotting Predicted Run-Off Diagonal
One-year-ahead prediction based on PARALLAX, REACT, or MACRAME
Print Objects of the S3 Class mcSetup
Print Objects of the S3 Class permutedReserve
Print Objects of the S3 Class profileLadder
Print Objects of the S3 Class profilePredict
Set Custom Color Styles for profileLadder Output
Summary Method for the S3 Class Object mcSetup
Summary Method for the S3 Objects permutedReserve
Summary Method for Objects of the S3 Class Method profileLadder
Functional claims reserving methods based on aggregated chain-ladder data, also known as a run-off triangle, implemented in three nonparametric algorithms (PARALLAX, REACT, and MACRAME) proposed in Maciak, Mizera, and Pešta (2022) <doi:10.1017/asb.2022.4>. Additional methods including permutation bootstrap for completed run-off triangles are also provided.
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