hierCredTweedie {actuaRE}  R Documentation 
Combining the hierarchical credibility model with a GLM (Ohlsson, 2008)
Description
Fit a random effects model using Ohlsson's methodology. In this function you estimate the power parameter p. See hierCredGLM
when
you want fix p.
Usage
hierCredTweedie(
formula,
data,
weights,
muHatGLM = TRUE,
epsilon = 1e04,
maxiter = 500,
verbose = FALSE,
returnData = TRUE,
cpglmControl = list(bound.p = c(1.01, 1.99)),
balanceProperty = TRUE,
optimizer = "bobyqa",
y = TRUE,
...
)
Arguments
formula 
object of type 
data 
an object that is coercible by 
weights 
variable name of the exposure weight. 
muHatGLM 
indicates which estimate has to be used in the algorithm for the intercept term. Default is 
epsilon 
positive convergence tolerance 
maxiter 
maximum number of iterations. 
verbose 
logical indicating if output should be produced during the algorithm. 
returnData 
logical indicating if input data has to be returned. 
cpglmControl 
a list of parameters to control the fitting process in the GLM part. By default,

balanceProperty 
logical indicating if the balance property should be satisfied. 
optimizer 
a character string that determines which optimization routine is to be used in estimating the index and the dispersion parameters.
Possible choices are 
y 
logical indicating whether the response vector should be returned as a component of the returned value. 
... 
arguments passed to 
Details
When estimating the GLM part, this function uses the cpglm
function from the cplm
package.
Value
An object of type hierCredTweedie
with the following slots:
call 
the matched call 
HierarchicalResults 
results of the hierarchical credibility model. 
fitGLM 
the results from fitting the GLM part. 
iter 
total number of iterations. 
Converged 
logical indicating whether the algorithm converged. 
LevelsCov 
object that summarizes the unique levels of each of the contractspecific covariates. 
fitted.values 
the fitted mean values, resulting from the model fit. 
prior.weights 
the weights (exposure) initially supplied. 
y 
if requested, the response vector. Default is 
References
Ohlsson, E. (2008). Combining generalized linear models and credibility models in practice. Scandinavian Actuarial Journal 2008(4), 301–314.
See Also
hierCredTweedieclass
, fitted.hierCredTweedie
, predict.hierCredTweedie
, ranefactuaRE
,
weightsactuaRE
, hierCredibility
, hierCredGLM
, cpglm
, plotRE
,
adjustIntercept
, BalanceProperty
@references Campo, B.D.C. and Antonio, Katrien (2023). Insurance pricing with hierarchically structured data an illustration with a workers' compensation insurance portfolio. Scandinavian Actuarial Journal, doi: 10.1080/03461238.2022.2161413
Examples
data("dataCar")
fit = hierCredTweedie(Y ~ area + (1  VehicleType / VehicleBody), dataCar,
weights = w, epsilon = 1e6)
fit
summary(fit)
ranef(fit)
fixef(fit)