gamlss.data (version 5.1-4)

mvi: The motor vehicle insurance data

Description

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)

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 BMW DAEWOO FORD MITSUBISHI

vehbody

a factor showing the type of the cat, with levels BUS CONT COUPE HACK HDTOP HRSE MCARA MIBUS PANVN RDSTR SEDAN STNWG TRUCK UTE

vehage

a numeric vector showing the age of the car

gender

a factor showing the gender of the policy holder with levels F M

area

a factor showing the Area of residence of the policy holder with levels A B C D E F

agecat

a factor showing the age band of the policy holder with levels 1 2 3 4 5 6 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.

Examples

# NOT RUN {
data(mvi)
## a histogram of claims with fitted gamma disteibution
## library(gamlss)
## with(mvi, histDist(claimcst0[whetherclm==1&claimcst0<15000], family=GA, main="Claims"))
# }