hierCredibility-class.Rd
Class "hierCredibility" of fitted hierarchical credibility models
an object of class hierCredibility
currently ignored.
an object of class hierCredibility
The function hierCredibility
returns an object of class hierCredibility
, which has the following slots:
the matched call
Whether additive or multiplicative hierarchical credibility model is used.
The estimated variance components. s2
is the estimated variance of the individual contracts,
tausq
the estimate of \(Var(V[j])\) and nusq
is the estimate of \(Var(V[jk])\).
The estimated averages at the portfolio level (intercept term \(\mu\)), at the first hierarchical level (\(bar(Y)[\%.\% j \%.\% \%.\%]^z\)) and at the second hierarchical level (\(bar(Y)[\%.\% jk \%.\%]\)).
The weights at the first hierarchical level \(z[j\%.\%]\) and at the second hierarchical level \(w[\%.\%jk\%.\%]\).
The credibility weights at the first hierarchical level \(q[j\%.\%]\) and at the second hierarchical level \(z[jk]\).
The overall expectation \(widehat(\mu)\), sector expectation \(widehat(V)[j]\) and group expectation \(widehat(V)[jk]\).
The estimated random effects \(widehat(U)[j]\) and \(widehat(U)[jk]\) of the sector and group, respectively.
Objects of type data.table
with all intermediate results.
the fitted mean values, resulting from the model fit.
print
:Prints the call
, the estimated variance parameters and the unique number of categories
of the hierarchical MLF. The ...
argument is currently ignored. Returns an invisible copy of the original
object.
summary
:In addition to the output of the print.hierCredibility
function, the summary
function
prints the random effect estimates as well. Returns an invisible copy of the original object.
fitted
:Returns the fitted values.