DCL: Claims Reserving under the Double Chain Ladder Model

Statistical modelling and forecasting in claims reserving in non-life insurance under the Double Chain Ladder framework by Martinez-Miranda, Nielsen and Verrall (2012).

AuthorMaria Dolores Martinez-Miranda, Jens Perch Nielsen and Richard Verrall
Date of publication2013-10-25 07:16:10
MaintainerMaria Dolores Martinez-Miranda <mmiranda@ugr.es>

View on CRAN

Man pages

Aggregate: Switch to a higher level of aggregation

bdcl.estimation: Parameter estimation - DCL model using the BDCL method

clm: Classical Chain Ladder Method

dcl.boot: Bootstrap distribution: the full cashflow

dcl.boot.prior: Bootstrap distribution (the full cashflow) adding prior...

dcl.estimation: Parameter estimation - Double Chain Ladder model

DCL-package: Claims Reserving under the Double Chain Ladder Model

dcl.predict: Pointwise predictions (RBNS/IBNR split)

dcl.predict.prior: Pointwise predictions (RBNS/IBNR split) adding prior...

extract.prior: Extracting information about zero-claims and severity...

get.cumulative: Cumulative triangle

get.incremental: Incremental triangle

idcl.estimation: Parameter estimation - DCL model reproducing the incurred...

ItriangleBDCL: Incurred data (BDCL example)

NpaidPrior: Number of non-zero payments (adding prior knowledge example)

NtriangleBDCL: Number of reported claims (BDCL example)

NtriangleDCL: Number of reported claims (DCL example)

NtrianglePrior: Number of reported claims (adding prior knowledge example)

Plot.cashflow: Plotting the full cashflow (bootstrap distribution)

Plot.clm.par: Plotting the estimated chain ladder parameters

Plot.dcl.par: Plotting the estimated parameters in the DCL model

Plot.triangle: Plotting an incremental run-off triangle

validating.incurred: Back-test: testing against the experience

XtriangleBDCL: Paid data (BDCL example)

XtriangleDCL: Paid data (DCL example)

XtrianglePrior: Paid data (adding prior knowledge example)

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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