R Dataset / Package COUNT / nuts

Submitted by pmagunia on March 9, 2018 - 1:06 PM
Dataset License
GNU General Public License v2.0
Attachment Size
dataset-93028.csv 5.58 KB
Documentation

nuts

Description

Squirrel data set (nuts) from Zuur, Hilbe, and Ieno (2013). As originally reported by Flaherty et al (2012), researchers recorded information about squirrel behavior and forest attributes across various plots in Scotland's Abernathy Forest. The study focused on the following variables. response cones number of cones stripped by red squirrels per plot predictor sntrees standardized number of trees per plot sheight standardized mean tree height per plot scover standardized percentage of canopy cover per plot The stripped cone count was only taken when the mean diameter of trees was under 0.6m (dbh).

Usage

data(nuts)

Format

A data frame with 52 observations on the following 8 variables.

cones

number cones stripped by squirrels

ntrees

number of trees per plot

dbh

number DBH per plot

height

mean tree height per plot

cover

canopy closure (as a percentage)

sntrees

standardized number of trees per plot

sheight

standardized mean tree height per plot

scover

standardized canopy closure (as a percentage)

Details

nuts is saved as a data frame. Count models use ntrees as response variable. Counts start at 3

Source

Zuur, Hilbe, Ieno (2013), A Beginner's Guide to GLM and GLMM using R, Highlands

References

Hilbe, Joseph M (2014), Modeling Count Data, Cambridge University Press Zuur, Hilbe, Ieno (2013), A Beginner's Guide to GLM and GLMM using R, Highlands. Flaherty, S et al (2012), "The impact of forest stand structure on red squirrels habitat use", Forestry 85:437-444.

Examples

data(nuts)
nut <- subset(nuts, dbh < 0.6)
# sntrees <- scale(nuts$ntrees)
# sheigtht <- scale(nuts$height)
# scover <- scale(nuts$cover)
summary(PO <- glm(cones ~ sntrees + sheight + scover, family=quasipoisson, data=nut))
--

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

Documentation License
GNU General Public License v2.0

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