R Dataset / Package COUNT / ships

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<iframe src="https://embed.picostat.com/r-dataset-package-count-ships.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-26989.csv 738 bytes
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
Dataset Help

On this Picostat.com statistics page, you will find information about the ships data set which pertains to ships. The ships data set is found in the COUNT R package. You can load the ships data set in R by issuing the following command at the console data("ships"). This will load the data into a variable called ships. If R says the ships data set is not found, you can try installing the package by issuing this command install.packages("COUNT") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the ships R data set. The size of this file is about 738 bytes.

Documentation

ships

Description

Data set used in McCullagh & Nelder (1989), Hardin & Hilbe (2003), and other sources. The data contains values on the number of reported accidents for ships belonging to a company over a given time period. When a ship was constructed is also recorded.

Usage

data(ships)

Format

A data frame with 40 observations on the following 7 variables.

accident

number of shipping accidents

op

1=ship operated 1975-1979;0=1965-74

co.65.69

ship was in construction 1965-1969 (1/0)

co.70.74

ship was in construction 1970-1974 (1/0)

co.75.79

ship was in construction 1975-1979 (1/0)

service

months in service

ship

ship identification : 1-5

Details

ships is saved as a data frame. Count models use accident as the response variable, with log(service) as the offset. ship can be used as a panel identifier.

Source

McCullagh and Nelder, 1989.

References

Hilbe, Joseph M (2007, 2011), Negative Binomial Regression, Cambridge University Press Hilbe, Joseph M (2009), Logistic Regression Models, Chapman & Hall/CRC Hardin, JW and JM Hilbe (2001, 2007), Generalized Linear Models and Extensions, Stata Press McCullagh, P.A, and J. Nelder (1989), Generalized Linear Models, Chapman & Hall

Examples

data(ships)
glmshp <- glm(accident ~ op + co.70.74 + co.75.79 + offset(log(service)),
              family=poisson, data=ships)
summary(glmshp)
exp(coef(glmshp))
library(MASS)
glmshnb <- glm.nb(accident ~ op + co.70.74 + co.75.79 + offset(log(service)),
                   data=ships)
summary(glmshnb)
exp(coef(glmshnb))
## Not run: 
library(gee)
shipgee <- gee(accident ~ op + co.70.74 + co.75.79 + offset(log(service)),
              data=ships, family=poisson, corstr="exchangeable", id=ship)
summary(shipgee)## End(Not run)
--

Dataset imported from https://www.r-project.org.

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