qpaid {ChainLadder} | R Documentation |
Sample data to demonstrate how to work with triangles with a higher development period frequency than origin period frequency
data(qpaid); data(qincurred)
A matrix with 12 accident years and 45 development quarters of claims costs.
Made up data for testing purpose
dim(qpaid) dim(qincurred) op=par(mfrow=c(1,2)) ymax <- max(c(qpaid,qincurred),na.rm=TRUE)*1.05 matplot(t(qpaid), type="l", main="Paid development", xlab="Dev. quarter", ylab="$", ylim=c(0,ymax)) matplot(t(qincurred), type="l", main="Incurred development", xlab="Dev. quarter", ylab="$", ylim=c(0,ymax)) par(op) ## MackChainLadder expects a quadratic matrix so let's expand ## the triangle to a quarterly origin period. n <- ncol(qpaid) Paid <- matrix(NA, n, n) Paid[seq(1,n,4),] <- qpaid M <- MackChainLadder(Paid) plot(M) # We expand the incurred triangle in the same way Incurred <- matrix(NA, n, n) Incurred[seq(1,n,4),] <- qincurred # With the expanded triangles we can apply MunichChainLadder MunichChainLadder(Paid, Incurred) # In the same way we can apply BootChainLadder # We reduce the resample size R from the default of 999 to 99 in this example purely to reduce run time. BootChainLadder(Paid, R=99)