R Dataset / Package COUNT / loomis
On this Rdata statistics page, you will find information about the loomis data set which pertains to loomis. The loomis data set is found in the COUNT R package. You can load the loomis data set in R by issuing the following command at the console data("loomis"). This will load the data into a variable called loomis. If R says the loomis 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 with the library() command. 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 loomis R data set. The size of this file is about 9,685 bytes.
loomis
Description
Data are taken from Loomis (2003). The study relates to a survey taken on reported frequency of visits to national parks during the year. The survey was taken at park sites, thus incurring possible effects of endogenous stratification.
Usage
data(loomis)
Format
A data frame with 410 observations on the following 11 variables.
anvisits

number of annual visits to park
gender

1=male;0=female
income

income in US dollars per year, categorical: 4 levels
income1

<=$25000
income2

>$25000  $55000
income3

>$55000  $95000
income4

>$95000
travel

travel time, categorical: 3 levels
travel1

<.25 hrs
travel2

>=.25  <4 hrs
travel3

>=4 hrs
Details
loomis is saved as a data frame. Count models typically use anvisits as response variable. 0 counts are included
Source
from Loomis (2003)
References
Hilbe, Joseph M (2007, 2011), Negative Binomial Regression, Cambridge University Press Loomis, J. B. (2003). Travel cost demand model based river recreation benefit estimates with onsite and household surveys: Comparative results and a correction procedure, Water Resources Research, 39(4): 1105
Examples
data(loomis) glmlmp < glm(anvisits ~ gender + factor(income) + factor(travel), family=poisson, data=loomis) summary(glmlmp) exp(coef(glmlmp)) library(MASS) glmlmnb < glm.nb(anvisits ~ gender + factor(income) + factor(travel), data=loomis) summary(glmlmnb) exp(coef(glmlmnb))
Dataset imported from https://www.rproject.org.