R: Data sets in the cplm pakcage

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.

[Package cplm version 0.7-8 Index]