tailFactor: A generic function to plot and/or return the predicted tail...
In BALD: Robust Loss Development Using MCMC

Description Arguments Details Value See Also Examples

A generic function to plot and/or return the predicted tail factors for a specific attachment point.

`object`	The object from which to plot the predicted tail factors and return tail factors for all attachment points.
`attachment`	An integer value specifying the attachment point for the tail. Must be at least 1. See Details for more information.
`useObservedValues`	A logical value. If `TRUE`, observed values are substituted for predicted values whenever possible in the calculation. If `FALSE`, only predicted values are used.
`firstIsHalfReport`	A logical value or `NA`. See Details for more info.
`finalAttachment`	An integer value must be at least 1. Default value is `attachment`. A call to `tailFactor` will return (invisibly) a matrix of tail factors through this value.
`plot`	A logical value. If `TRUE`, the plot is generated and the statistics are returned; otherwise only the statistics are returned.
`expYearRange`	Either a range of years (for example c(1995, 2006)) or one of the keywords “all” or “fullyObs”.

The tail factor is the ratio of the estimated ultimate loss to cumulative loss at some point in development time. This is a generic function to allow for the retrieval and illustration the tail factor by exposure year.

Note on firstIsHalfReport and attachment: firstIsHalfReport refers to the first column of the triangle. For policy year triangles, the first column is often referred to as a “half-report”, the second column is called “first-report”, the third column is called “second-report”, etc. If firstIsHalfReport=TRUE, then tailFactor will assume the triangle is arranged in such a way that the first column is the “half-report” and attachment=1 indicates that the charted tail factor attaches at the cumulative loss through the second column. If firstIsHalfReport=FALSE, then attachment=1 indicates that the charted tail factor attaches at the cumulative loss through the first column. Since attachment must be coercible to an integer, it is impossible to plot half-to-ultimate tail factors; however, they are the first column in the returned matrix.

firstIsHalfReport can be NA (the default) if the exposure year type was specified to be one of “policy year” or “accident year” at the time the input object was constructed (see makeStandardAnnualInput or makeBreakAnnualInput). An exposure year type of “policy year” corresponds to firstIsHalfReport=TRUE, and an exposure year type of “accident year” corresponds to firstIsHalfReport=FALSE. Setting firstIsHalfReport to a non-missing value will override this default.

If expYearRange is “fullyObs”, then only exposure years with a non missing value in the first column will be plotted. See vignette('BALD').

Mainly called for the side effect of plotting.

tailFactor("StandardAnnualAggLossDevModelOutput") tailFactor("BreakAnnualAggLossDevModelOutput")

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)
tailFactor(standard.model.output,10)

## End(Not run)