datasets: Data sets in the cplm pakcage

In cplm: Compound Poisson Linear Models

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 documentation built on Sept. 21, 2024, 9:06 a.m.