| mvi | R Documentation |
The motor vehicle insurance data are motor vehicle insurance policies.
mvi is a sample of 2000 observations from mviBig which has 67143 observartions
data(mvi)
data(mviBig)
Two data frames with 2000 or 67143 observations on the following 14 variables.
retvala numeric vector showing the value of the vehicle
whetherclma numeric vector showing whether a claim is made, 0 no claim, 1 at least one claim
numclaimsa nuneric vactor showing the number of claims
claimcst0a numeric vector showing the total amount of claim, i.e. for numclaims=0 is zero.
vehmakea factor showing the make of the car with levels BMW DAEWOO FORD MITSUBISHI
vehbodya factor showing the type of the cat, with levels BUS CONT COUPE HACK
HDTOP HRSE MCARA MIBUS PANVN RDSTR SEDAN STNWG TRUCK UTE
vehagea numeric vector showing the age of the car
gendera factor showing the gender of the policy holder with levels F M
areaa factor showing the Area of residence of the policy holder with levels A B C D E F
agecata factor showing the age band of the policy holder with levels 1 2 3 4 5 6 one is youngest
exposurea numeric vector showing the time of exposure with values from zero to one
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.
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"))
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