ChainLadder (version 0.1.1-1)

predict.TriangleModel: Prediction of a claims triangle

Description

The function is internally used by MackChainLadder to forecast future claims.

Usage

## S3 method for class 'TriangleModel':
predict(object,...)

Arguments

object

a list with two items: Models, Triangle [object Object],[object Object]

Value

• FullTriangle
  forecasted claims triangle

item

...

See Also

See Also MackChainLadder

Examples

RAA <- t(matrix(c(
  5012,  8269, 10907, 11805, 13539, 16181, 18009, 18608, 18662, 18834,
   106,  4285,  5396, 10666, 13782, 15599, 15496, 16169, 16704,    NA,
  3410,  8992, 13873, 16141, 18735, 22214, 22863, 23466,    NA,    NA,
  5655, 11555, 15766, 21266, 23425, 26083, 27067,    NA,    NA,    NA,
  1092,  9565, 15836, 22169, 25955, 26180,    NA,    NA,    NA,    NA,
  1513,  6445, 11702, 12935, 15852,    NA,    NA,    NA,    NA,    NA,
   557,  4020, 10946, 12314,    NA,    NA,    NA,    NA,    NA,    NA,
  1351,  6947, 13112,    NA,    NA,    NA,    NA,    NA,    NA,    NA,
  3133,  5395,    NA,    NA,    NA,    NA,    NA,    NA,    NA,    NA,
  2063,    NA,    NA,    NA,    NA,    NA,    NA,    NA,    NA,    NA
  ), ncol=10))
    
 MCL=MackChainLadder(RAA)
 MCL
 plot(MCL)
 MCL[["Models"]][[1]]   # Model for first development period
 summary( MCL[["Models"]][[1]]) # Look at the model stats
 op=par(mfrow=c(2,2)) # plot residuals
   plot( MCL[["Models"]][[1]])
 par(op)

 # Let's include an intercept in our model
 newModel <- update(MCL[["Models"]][[1]], y ~ x+1, 
              weights=1/MCL[["Triangle"]][1:9,1],
              data=data.frame(x=MCL[["Triangle"]][1:9,1], 
                              y=MCL[["Triangle"]][1:9,2])
               ) 

# view the new model
 summary(newModel)
 op=par(mfrow=c(2,2)) 
   plot( newModel )
 par(op)

 # change the model for dev. period one to the newModel
 MCL2=MCL
 MCL2[["Models"]][[1]] = newModel
 predict(MCL2) # predict the full triangle with the new model 
 #(only the last origin year will be affected)

 MCL2[["FullTriangle"]] <-  predict(MCL2)
 MCL2[["FullTriangle"]] 
 MCL2   # Std. Errors have not been re-estimated!
 # plot the res
 
 plot(MCL2, title="Change MCL Model")