consumptionPath {BALD} | R Documentation |
A generic function to plot and/or return the estimated consumption path vs development year time.
object |
The object from which to plot and/or return the estimated consumption path. |
plot |
A logical value. If |
At the heart of aggregate loss development models in BALD is the consumption path.
The consumption path is (on a log scale) the trajectory of incremental payments absent calendar year effects and with exposure normalized to the first row.
Note that the measurement error term is (possibly) a skewed t and as such (possibly) has a non zero mean. The consumption path is absent any such shifts due to skewness.
This is a generic function that allows for the retrieval and illustration of this consumption path.
See vignette('BALD')
.
Mainly called for the side effect of plotting. Also returns the plotted statistics. Returned invisibly.
consumptionPath("StandardAnnualAggLossDevModelOutput")
consumptionPath("BreakAnnualAggLossDevModelOutput")
consumptionPathTracePlot
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) consumptionPath(standard.model.output) ## End(Not run)