predictedPayments {BALD} | R Documentation |

A generic function to plot predicted vs actual payments for models from the BALD package.

`object` |
The object from which to plot predicted vs actual payments and from which to return predicted payments. |

`type` |
A single character value specifying whether to plot/return the predicted incremental or cumulative payments. Valid values are “incremental” or “cumulative.” See details as to why these may not match up. |

`logScale` |
A logical value. If |

`mergePredictedWithObserved` |
A logical value. See details. |

`plotObservedValues` |
A logical value. If |

`plotPredictedOnlyWhereObserved` |
A logical value. If |

`quantiles` |
A vector of quantiles for the predicted payments to return. Useful for constructing credible intervals. |

`plot` |
A logical value. If |

Because the model is Bayesian, each estimated payment comes as a distribution. The median of this distribution is used as a point estimate when plotting and/or returning values. Note: One cannot calculate the estimated incremental payments from the estimated cumulative payments (and vice versa) since the median of sums need not be equal to the sum of medians.

If `mergePredictedWithObserved=TRUE`

and `type="incremental"`

, then any observed incremental payment will be used in place of its corresponding incremental payment.
If `mergePredictedWithObserved=TRUE`

and `type="cumulative"`

, then only predicted incremental payments (by row) to the right of the last observed cumulative value will enter the calculation.
See `vignette('BALD')`

.

Mainly called for the side effect of plotting.

`predictedPayments("AnnualAggLossDevModelOutput")`

rm(list=ls()) options(device.ask.default=FALSE) library(BALD) data(IncrementalGeneralLiablityTriangle) IncrementalGeneralLiablityTriangle <- as.matrix(IncrementalGeneralLiablityTriangle) print(IncrementalGeneralLiablityTriangle) data(PCE) PCE <- as.matrix(PCE)[,1] PCE.rate <- PCE[-1] / PCE[-length(PCE)] - 1 PCE.rate.length <- length(PCE.rate) PCE.years <- as.integer(names(PCE.rate)) years.available <- PCE.years <= max(as.integer( dimnames(IncrementalGeneralLiablityTriangle)[[1]])) PCE.rate <- PCE.rate[years.available] PCE.rate.length <- length(PCE.rate) standard.model.input <- makeStandardAnnualInput( incremental.payments = IncrementalGeneralLiablityTriangle, stoch.inflation.weight = 1, non.stoch.inflation.weight = 0, stoch.inflation.rate = PCE.rate, exp.year.type = 'ay', extra.dev.years=5, use.skew.t=TRUE) ## Not run: standard.model.output <- runLossDevModel( standard.model.input, burnIn=30.0E+3, sampleSize=30.0E+3, thin=10) predictedPayments(standard.model.output) ## End(Not run)

[Package *BALD* version 1.0.0-3 Index]