# Automobile Bodily Injury Claims

### Description

Data from the Insurance Research Council (IRC), a division of the American Institute for Chartered Property Casualty Underwriters and the Insurance Institute of America. The data, collected in 2002, contains information on demographic information about the claimant, attorney involvement and the economic loss (LOSS, in thousands), among other variables. We consider here a sample of n = 1; 340 losses from a single state. The full 2002 study contains over 70,000 closed claims based on data from thirty-two insurers. The IRC conducted similar studies in 1977, 1987, 1992 and 1997.

### Usage

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### Format

A data frame with 1340 observations on the following 8 variables.

`CASENUM`

Case number to identify the claim, a numeric vector

`ATTORNEY`

Whether the claimant is represented by an attorney (=1 if yes and =2 if no), a numeric vector

`CLMSEX`

Claimant's gender (=1 if male and =2 if female), a numeric vector

`MARITAL`

claimant's marital status (=1 if married, =2 if single, =3 if widowed, and =4 if divorced/separated), a numeric vector

`CLMINSUR`

Whether or not the driver of the claimant's vehicle was uninsured (=1 if yes, =2 if no, and =3 if not applicable), a numeric vector

`SEATBELT`

Whether or not the claimant was wearing a seatbelt/child restraint (=1 if yes, =2 if no, and =3 if not applicable), a numeric vector

`CLMAGE`

Claimant's age, a numeric vector

`LOSS`

The claimant's total economic loss (in thousands), a numeric vector

### Details

http://instruction.bus.wisc.edu/jfrees/jfreesbooks/Regression%20Modeling/BookWebDec2010/

DataDescriptions.pdf

### Source

http://instruction.bus.wisc.edu/jfrees/jfreesbooks/Regression%20Modeling/BookWebDec2010/data.html

### References

Frees E.W. (2010), Regression Modeling with Actuarial and Financial Applications, Cambridge University Press.

### Examples

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