summary-methods {ChainLadder} | R Documentation |
Methods for function summary
to calculate summary statistics from a "MultiChainLadder" object.
## S4 method for signature 'MultiChainLadder' summary(object, portfolio=NULL,...)
object |
object of class |
portfolio |
character strings specifying which triangles to be summed up as portfolio. |
... |
optional arguments to |
summary
calculations the summary statistics for each triangle and the whole portfolio from portfolio
. portfolio
defaults to the sum of all input triangles. It can also be specified as "i+j" format, which means the sum of the i-th and j-th triangle as portfolio. For example, "1+3"
means the sum of the first and third triangle as portfolio.
The summary
function returns an object of class "MultiChainLadderSummary" that has the following slots:
Triangles |
input triangles |
FullTriangles |
predicted triangles |
S.E.Full |
a list of prediction errors for each cell |
S.E.Est.Full |
a list of estimation errors for each cell |
S.E.Proc.Full |
a list of process errors for each cell |
Ultimate |
predicted ultimate losses for each triangle and portfolio |
Latest |
latest observed losses for each triangle and portfolio |
IBNR |
predicted IBNR for each triangle and portfolio |
S.E.Ult |
a matrix of prediction errors of ultimate losses for each triangle and portfolio |
S.E.Est.Ult |
a matrix of estimation errors of ultimate losses for each triangle and portfolio |
S.E.Proc.Ult |
a matrix of process errors of ultimate losses for each triangle and portfolio |
report.summary |
summary statistics for each triangle and portfolio |
coefficients |
estimated coefficients from |
coefCov |
estimated variance-covariance matrix returned by |
residCov |
estimated residual covariance matrix returned by |
rstandard |
standardized residuals |
fitted.values |
fitted.values |
residCor |
residual correlation |
model.summary |
summary statistics for the cofficients including p-values |
portfolio |
how portfolio is calculated |
Wayne Zhang actuary_zhang@hotmail.com
See Also MultiChainLadder
data(GenIns) fit.bbmw=MultiChainLadder(list(GenIns),fit.method="OLS", mse.method="Independence") summary(fit.bbmw)