datasets {cplm} | R Documentation |

## Data sets in the cplm pakcage

### Description

The data sets included in package is described here.

### Usage

```
data(FineRoot)
data(ClaimTriangle)
data(AutoClaim)
```

### Format

`FineRoot`

: a data set used for the study of the fine root length density of plants. It is a data frame with 511 records and 5 variables:

`Plant`

:identifier of the apple tree, 1-8

`Stock`

:root stokcing, one of three different root stocks: Mark, MM106 and M26

`Spacing`

:between-row

`\times`

within-row spacings, one of the following two:`4 \times 2`

meters and`5 \times 3`

meters`Zone`

:inner or outer

`RLD`

:root length density

`ClaimTriangle`

: a data set from an insurance loss reserving triangle. It is a data frame with 55 records and 3 variables:

`year`

:the year when the accident occurs

`lag`

:development lag

`increLoss`

:incremental insurance loss in 1000s

`AutoClaim`

: a motor insurance data set retrieved from
the SAS Enterprise Miner database. It is a data frame with 10296 records and 29 variables:

`POLICYNO`

:"character", the policy number

`PLCYDATE`

:"Date", policy effective date

`CLM_FREQ5`

:"integer", the number of claims in the past 5 years

`CLM_AMT5`

:"integer", the total claim amount in the past 5 years

`CLM_AMT`

:"integer", the claim amount in the current insured period

`KIDSDRIV`

:"integer", the number of driving children

`TRAVTIME`

:"integer", the distance to work

`CAR_USE`

:"factor", the primary use of the vehicle: "Commercial", "Private".

`BLUEBOOK`

:"integer", the value of the vehicle

`RETAINED`

:"integer", the number of years as a customer

`NPOLICY`

:"integer", the number of policies

`CAR_TYPE`

:"factor", the type of the car: "Panel Truck", "Pickup", "Sedan", "Sports Car", "SUV", "Van".

`RED_CAR`

:"factor", whether the color of the car is red: "no", "yes".

`REVOLKED`

:"factor", whether the dirver's license was invoked in the past 7 years: "No", "Yes",

`MVR_PTS`

:"integer", MVR violation records

`CLM_FLAG`

:"factor", whether a claim is reported: "No", "Yes".

`AGE`

:"integer", the age of the driver

`HOMEKIDS`

:"integer", the number of children

`YOJ`

:"integer", years at current job

`INCOME`

:"integer", annual income

`GENDER`

:"factor", the gender of the driver: "F", "M".

`MARRIED`

:"factor", married or not: "No", "Yes".

`PARENT1`

:"factor", single parent: "No", "Yes".

`JOBCLASS`

:"factor": "Unknown", "Blue Collar", "Clerical", "Doctor", "Home Maker", "Lawyer", "Manager", "Professional", "Student".

`MAX_EDUC`

:"factor", max education level:"<High School", "Bachelors", "High School", "Masters", "PhD".

`HOME_VAL`

:"integer", the value of the insured's home

`SAMEHOME`

:"integer", years in the current address

`DENSITY`

:"factor", home/work area: "Highly Rural", "Highly Urban", "Rural", "Urban".

`IN_YY`

:"logical", whether the record is used in the Yip and Yau (2005) paper.

### Source

de Silva, H. N., Hall, A. J., Tustin, D. S. and Gandar, P. W. (1999). Analysis of distribution
of root length density of apple trees on different dwarfing rootstocks. *Annals of
Botany*, 83: 335-345.

Dunn, P.K. and Smyth, G.K. (2005). Series evaluation of Tweedie exponential dispersionmodels densities. *Statistics and Computing*, 15, 267-280.

Peters G. W., Shevchenko P. V. and Wuthrich M. V. (2009). Model Uncertainty in Claims Reserving within Tweedie's Compound Poisson Models. *Astin Bulletin*, 39(1), 1-33.

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(2), 153-163.

*cplm*version 0.7-12 Index]