DCL (version 0.1.2)

Plot.triangle: Plotting an incremental run-off triangle

Description

Graphical representaion of an incremental run-off triangle.

Usage

Plot.triangle( triangle , Histogram = FALSE , tit='' )

Arguments

triangle

The loss incremental triangle. It should be a matrix with the observed counts (number of reported claims, number of payments etc.), payments or incurred data, located in the upper triangle. The lower triangle consisting in missing or zero values.

Histogram

Logical. If TRUE then a histogram representing the triangle is shown. If FALSE (default) then a classical representation of the triangle is shown, this is, a matplot of the row sums from both incremental and cummulative triangle.

tit

Character. Title to be added to the plot

Value

No returned value

Details

A histogram representation of the histogram is consistent with the run-off triangles of counts such as the number of reported claims, number of payments, etc. See Martinez-Miranda, Nielsen, Sperlich and Verrall (2013) for a further explanation.

References

Martinez-Miranda, M.D., Nielsen, J.P. and Verrall, R. (2012) Double Chain Ladder. Astin Bulletin, 42/1, 59-76.

Martinez-Miranda M.D., Nielsen, J.P., Sperlich, S., Verrall, R. (2013). Continuous Chain Ladder: Reformulating and generalizing a classical insurance problem. Experts Systems with Applications, 40(14), 5588-5603.

See Also

get.incremental, clm

Examples

# NOT RUN {
## Plotting a counts triangle (number of reported claims)
data(NtriangleDCL)
Plot.triangle(NtriangleDCL, Histogram=TRUE,tit=expression(paste('Counts: ',N[ij])))
# Classical CL predictions
clm.N<-clm(NtriangleDCL)
Nhat<-clm.N$triangle.hat
# Compare the original histogram with the CL projections
Plot.triangle(Nhat, Histogram=TRUE,tit='CL Predictions')

## Plotting a paid triangle (number of reported claims)
data(XtriangleDCL)
Plot.triangle(XtriangleDCL)
# }