AutoBi: Automobile Bodily Injury Claims

In insuranceData: A Collection of Insurance Datasets Useful in Risk Classification in Non-life Insurance.

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

data(AutoBi)

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

data(AutoBi)
## maybe str(AutoBi) ; plot(AutoBi) ...

Example output

insuranceData documentation built on May 2, 2019, 4:01 p.m.