This function extracts various summary statistics from distance sampling
data of various unmarkedFrame and unmarkedFit classes.
countDist(object, plot.freq = TRUE, plot.distance = TRUE, cex.axis = 1,
cex.lab = 1, cex.main = 1, ...)# S3 method for unmarkedFrameDS
countDist(object, plot.freq = TRUE,
plot.distance = TRUE, cex.axis = 1, cex.lab = 1,
cex.main = 1, ...)
# S3 method for unmarkedFitDS
countDist(object, plot.freq = TRUE,
plot.distance = TRUE, cex.axis = 1, cex.lab = 1,
cex.main = 1, ...)
# S3 method for unmarkedFrameGDS
countDist(object, plot.freq = TRUE,
plot.distance = TRUE, cex.axis = 1,
cex.lab = 1, cex.main = 1, ...)
# S3 method for unmarkedFitGDS
countDist(object, plot.freq = TRUE,
plot.distance = TRUE, cex.axis = 1,
cex.lab = 1, cex.main = 1, ...)
# S3 method for unmarkedFrameDSO
countDist(object, plot.freq = TRUE,
plot.distance = TRUE, cex.axis = 1,
cex.lab = 1, cex.main = 1, plot.seasons = FALSE,
...)
# S3 method for unmarkedFitDSO
countDist(object, plot.freq = TRUE,
plot.distance = TRUE, cex.axis = 1,
cex.lab = 1, cex.main = 1, plot.seasons = FALSE,
...)
countDist returns a list with the following components:
a table with the frequency of each observed count pooled across distances classes.
a list of tables with the frequency of each season-specific count pooled across distance classes.
a table with the frequency of counts in each distance class across the entire sampling seasons.
a list of tables with the frequency of counts in each distance class for each primary period.
a character string of labels for the distance classes.
the number of distance classes.
a matrix where the rows correspond to each sampling
season and where columns consist of the number of sites sampled in
season \(t\) (sampled) and the number of sites with at
least one detection in season \(t\) (detected). For
multiseason data, the matrix includes the number of sites sampled in
season \(t - 1\) with colonizations observed in season \(t\)
(colonized), the number of sites sampled in season \(t -
1\) with extinctions observed in season \(t\) (extinct), the
number of sites sampled in season \(t - 1\) without changes
observed in season \(t\) (static), and the number of sites
sampled in season \(t\) that were also sampled in season \(t -
1\) (common).
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 (naive.occ). For
multiseason data, the matrix includes the proportion of sites
sampled in season \(t - 1\) with colonizations observed in season
\(t\) (naive.colonization), the proportion of sites
sampled in season \(t - 1\) with extinctions observed in season
\(t\) (naive.extinction), and the proportion of sites
sampled in season \(t - 1\) with no changes observed in season
\(t\).
the number of seasons (primary periods) in the data set.
the maximum number of visits per season in the data set.
an object of various unmarkedFrame or unmarkedFit
classes containing distance sampling data.
logical. Specifies if the count data (pooled across seasons and distance classes) should be plotted.
logical. Specifies if the counts in each distance class (pooled across seasons) should be plotted.
expansion factor influencing the size of axis annotations on plots produced by the function.
expansion factor influencing the size of axis labels on plots produced by the function.
expansion factor influencing the size of the main title above plots produced by the function.
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.
Marc J. Mazerolle
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 distance-sampling 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.
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 state-space 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 open-population hierarchical distance sampling model. Ecology 96, 325--331.
covDiag, detHist, detTime,
countHist, Nmix.chisq,
Nmix.gof.test
##modified example from ?distsamp
if (FALSE) {
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)
##Half-normal detection function
fm1 <- distsamp(~ 1 ~ 1, ltUMF)
##compute descriptive stats from model object
countDist(fm1)
}
}
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