The motor vehicle insurance data are motor vehicle insurance policies.
mvi is a sample of 2000 observations from mviBig which has 67143 observartions
Usage
data(mvi)
data(mviBig)
Arguments
Format
Two data frames with 2000 or 67143 observations on the following 14 variables.
retval
a numeric vector showing the value of the vehicle
whetherclm
a numeric vector showing whether a claim is made, 0 no claim, 1 at least one claim
numclaims
a nuneric vactor showing the number of claims
claimcst0
a numeric vector showing the total amount of claim, i.e. for numclaims=0 is zero.
vehmake
a factor showing the make of the car with levels BMWDAEWOOFORDMITSUBISHI
vehbody
a factor showing the type of the cat, with levels BUSCONTCOUPEHACKHDTOPHRSEMCARAMIBUSPANVNRDSTRSEDANSTNWGTRUCKUTE
vehage
a numeric vector showing the age of the car
gender
a factor showing the gender of the policy holder with levels FM
area
a factor showing the Area of residence of the policy holder with levels ABCDEF
agecat
a factor showing the age band of the policy holder with levels 123456 one is youngest
exposure
a numeric vector showing the time of exposure with values from zero to one
Details
The motor vehicle insurance data are motor vehicle insurance policies from an insurance
company over a twelve-month period in 2004-05. The original data are 67143 observation
but here we also include a random sample of 2000.
References
Heller, G. Stasinopoulos M and Rigby R.A. (2006)
The zero-adjusted Inverse Gaussian distribution as a model for
insurance claims. in Proceedings of the 21th International
Workshop on Statistial Modelling, eds J. Hinde, J. Einbeck and J.
Newell, pp 226-233, Galway, Ireland.
Heller G. Z., Stasinopoulos M.D., Rigby R. A. and de Jong P. (2007)
Mean and dispersion modeling for policy claims costs. To be published in the Scandinavian Actuarial Journal.
data(mvi)
## a histogram of claims with fitted gamma disteibution## library(gamlss)## with(mvi, histDist(claimcst0[whetherclm==1&claimcst0<15000], family=GA, main="Claims"))