nuts: nuts

In COUNT: Functions, Data and Code for Count Data

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))

Example output

Loading required package: msme
Loading required package: MASS
Loading required package: lattice
Loading required package: sandwich

Call:
glm(formula = cones ~ sntrees + sheight + scover, family = quasipoisson, 
    data = nut)

Deviance Residuals: 
   Min      1Q  Median      3Q     Max  
-6.581  -3.388  -1.385   1.488   7.324  

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)   2.6352     0.1546  17.041   <2e-16 ***
sntrees       0.2739     0.1068   2.566   0.0135 *  
sheight       0.2004     0.1734   1.156   0.2536    
scover        0.5280     0.2439   2.164   0.0355 *  
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for quasipoisson family taken to be 13.68122)

    Null deviance: 882.20  on 50  degrees of freedom
Residual deviance: 647.41  on 47  degrees of freedom
AIC: NA

Number of Fisher Scoring iterations: 5

COUNT documentation built on May 2, 2019, 2:37 a.m.