Description Usage Details Value References Examples
The motor insurance dataset is originially retrieved from the SAS Enterprise Miner database. The included dataset is generated by re-organization and transformation as described in Qian et al. (2013).
1 |
This data set contains 2812 policy samples with 56 predictors. See Qian et al. (2013) for a detailed description of the generation of these predictors. The response is the aggregate claim loss (in thousand dollars). The predictors are expanded from the following original variables:
CAR_TYPE
:car type, 6 categories
JOBCLASS
:job class, 8 categories
MAX_EDUC
:education level, 5 categories
KIDSDRIV
:number of children passengers
TRAVTIME
:time to travel from home to work
BLUEBOOK
:car value
NPOLICY
:number of policies
MVR_PTS
:motor vehicle record point
AGE
:driver age
HOMEKIDS
:number of children at home
YOJ
:years on job
INCOME
:income
HOME_VAL
:home value
SAMEHOME
:years in current address
CAR_USE
:whether the car is for commercial use
RED_CAR
:whether the car color is red
REVOLKED
:whether the driver's license was revoked in the past
GENDER
:gender
MARRIED
:whether married
PARENT1
:whether a single parent
AREA
:whether the driver lives in urban area
A list with the following elements:
x |
a [2812 x 56] matrix giving 2812 policy records with 56 predictors |
y |
the aggregate claim loss |
Yip, K. C. H. and Yau, K. K. W. (2005), “On Modeling Claim Frequency Data In General Insurance With Extra Zeros”, Insurance: Mathematics and Economics 36, 153-163.
Zhang, Y (2013). “cplm
: Compound Poisson Linear Models”. A vignette for R package cplm
. Available from http://cran.r-project.org/web/packages/cplm
Qian, W., Yang, Y., Yang, Y. and Zou, H. (2013), “Tweedie's Compound Poisson Model With Grouped Elastic Net,” submitted to Journal of Computational and Graphical Statistics.
1 2 3 4 5 6 7 8 9 10 11 |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.