countDist {AICcmodavg}  R Documentation 
Compute Summary Statistics from Distance Sampling Data
Description
This function extracts various summary statistics from distance sampling
data of various unmarkedFrame
and unmarkedFit
classes.
Usage
countDist(object, plot.freq = TRUE, plot.distance = TRUE, cex.axis = 1,
cex.lab = 1, cex.main = 1, ...)
## S3 method for class 'unmarkedFrameDS'
countDist(object, plot.freq = TRUE,
plot.distance = TRUE, cex.axis = 1, cex.lab = 1,
cex.main = 1, ...)
## S3 method for class 'unmarkedFitDS'
countDist(object, plot.freq = TRUE,
plot.distance = TRUE, cex.axis = 1, cex.lab = 1,
cex.main = 1, ...)
## S3 method for class 'unmarkedFrameGDS'
countDist(object, plot.freq = TRUE,
plot.distance = TRUE, cex.axis = 1,
cex.lab = 1, cex.main = 1, ...)
## S3 method for class 'unmarkedFitGDS'
countDist(object, plot.freq = TRUE,
plot.distance = TRUE, cex.axis = 1,
cex.lab = 1, cex.main = 1, ...)
## S3 method for class 'unmarkedFrameDSO'
countDist(object, plot.freq = TRUE,
plot.distance = TRUE, cex.axis = 1,
cex.lab = 1, cex.main = 1, plot.seasons = FALSE,
...)
## S3 method for class 'unmarkedFitDSO'
countDist(object, plot.freq = TRUE,
plot.distance = TRUE, cex.axis = 1,
cex.lab = 1, cex.main = 1, plot.seasons = FALSE,
...)
Arguments
object 
an object of various 
plot.freq 
logical. Specifies if the count data (pooled across seasons and distance classes) should be plotted. 
plot.distance 
logical. Specifies if the counts in each distance class (pooled across seasons) should be plotted. 
cex.axis 
expansion factor influencing the size of axis annotations on plots produced by the function. 
cex.lab 
expansion factor influencing the size of axis labels on plots produced by the function. 
cex.main 
expansion factor influencing the size of the main title above plots produced by the function. 
plot.seasons 
logical. Specifies if the count data should be plotted for each distance class and season separately. This argument is only relevant for data collected across more than a single season. 
... 
additional arguments passed to the function. 
Details
This function computes a number of summary statistics in data sets used for the distance sampling models of Royle et al. (2004), Chandler et al. (2011), and distancesampling versions of models of Dail and Madsen (2011) and Hostetler and Chandler (2015) based on Sollmann et al. (2015).
countDist
can take data frames of the
unmarkedFrameDS
, unmarkedFrameGDS
,
unmarkedFrameDSO
classes as input. For convenience, the
function can also extract the raw data from model objects of classes
unmarkedFitDS
, unmarkedFitGDS
, and
unmarkedFitDSO
. Note that different model objects using the
same data set will have identical values.
Value
countDist
returns a list with the following components:
count.table.full 
a table with the frequency of each observed count pooled across distances classes. 
count.table.seasons 
a list of tables with the frequency of each seasonspecific count pooled across distance classes. 
dist.sums.full 
a table with the frequency of counts in each distance class across the entire sampling seasons. 
dist.table.seasons 
a list of tables with the frequency of counts in each distance class for each primary period. 
dist.names 
a character string of labels for the distance classes. 
n.dist.classes 
the number of distance classes. 
out.freqs 
a matrix where the rows correspond to each sampling
season and where columns consist of the number of sites sampled in
season 
out.props 
a matrix where the rows correspond to each sampling
season and where columns consist of the proportion of sites in
season t with at least one detection ( 
n.seasons 
the number of seasons (primary periods) in the data set. 
n.visits.season 
the maximum number of visits per season in the data set. 
missing.seasons 
logical vector indicating whether data were
collected or not during a given season (primary period), where

Author(s)
Marc J. Mazerolle
References
Chandler, R. B., Royle, J. A., King, D. I. (2011) Inference about density and temporary emigration in unmarked populations. Ecology 92, 1429–1435.
Dail, D., Madsen, L. (2011) Models for estimating abundance from repeated counts of an open population. Biometrics 67, 577–587.
Hostetler, J. A., Chandler, R. B. (2015) Improved statespace models for inference about spatial and temporal variation in abundance from count data. Ecology 96, 1713–1723.
Royle, J. A., Dawson, D. K., Bates, S. (2004) Modeling abundance effects in distance sampling. Ecology 85, 1591–1597.
Sollmann, R., Gardner, B., Chandler, R. B., Royle, J. A., Sillett, T. S. (2015) An openpopulation hierarchical distance sampling model. Ecology 96, 325–331.
See Also
covDiag
, detHist
, detTime
,
countHist
, Nmix.chisq
,
Nmix.gof.test
Examples
##modified example from ?distsamp
## Not run:
if(require(unmarked)){
data(linetran)
##format data
ltUMF < with(linetran, {
unmarkedFrameDS(y = cbind(dc1, dc2, dc3, dc4),
siteCovs = data.frame(Length, area, habitat),
dist.breaks = c(0, 5, 10, 15, 20),
tlength = linetran$Length * 1000, survey = "line",
unitsIn = "m")
})
##compute descriptive stats from data object
countDist(ltUMF)
##Halfnormal detection function
fm1 < distsamp(~ 1 ~ 1, ltUMF)
##compute descriptive stats from model object
countDist(fm1)
}
## End(Not run)