| detHist {AICcmodavg} | R Documentation |
Compute Summary Statistics from Detection Histories
Description
This function extracts various summary statistics from detection history
data of various unmarkedFrame and unmarkedFit classes.
Usage
detHist(object, ...)
## S3 method for class 'unmarkedFitColExt'
detHist(object, ...)
## S3 method for class 'unmarkedFitOccu'
detHist(object, ...)
## S3 method for class 'unmarkedFitOccuFP'
detHist(object, ...)
## S3 method for class 'unmarkedFitOccuRN'
detHist(object, ...)
## S3 method for class 'unmarkedFitOccuMulti'
detHist(object, ...)
## S3 method for class 'unmarkedFitOccuMS'
detHist(object, ...)
## S3 method for class 'unmarkedFrameOccu'
detHist(object, ...)
## S3 method for class 'unmarkedFrameOccuFP'
detHist(object, ...)
## S3 method for class 'unmarkedMultFrame'
detHist(object, ...)
## S3 method for class 'unmarkedFrameOccuMulti'
detHist(object, ...)
## S3 method for class 'unmarkedFrameOccuMS'
detHist(object, ...)
Arguments
object |
an object of various |
... |
additional arguments passed to the function. |
Details
This function computes a number of summary statistics in data sets used for single-season occupancy models (MacKenzie et al. 2002), dynamic occupancy models (MacKenzie et al. 2003), Royle-Nichols models (Royle and Nichols 2003), false-positive occupancy models (Royle and Link 2006, Miller et al. 2011), multispecies occupancy models (Rota et al. 2016), and multistate occupancy models (Nichols et al. 2007, MacKenzie et al. 2009).
detHist can take data frames of the unmarkedFrameOccu,
unmarkedFrameOccuFP, unmarkedMultFrame,
unmarkedFrameOccuMulti, unmarkedFrameOccuMS classes as
input. For convenience, the function can also extract the raw data
from model objects of classes unmarkedFitColExt,
unmarkedFitOccu, unmarkedFitOccuFP,
unmarkedFitOccuRN, unmarkedFrameOccuMulti, and
unmarkedFrameOccuMS. Note that different model objects using
the same data set will have identical values.
Value
For objects of classes unmarkedFitOccu, unmarkedFitOccuRN,
unmarkedFitOccuFP, unmarkedFitColExt,
unmarkedFitOccuMS, unmarkedFrameOccu,
unmarkedFrameOccuFP, unmarkedMultFrame, and
unmarkedFrameOccuMS, detHist returns a list with the
following components:
hist.table.full |
a table with the frequency of each observed detection history. |
hist.table.seasons |
a list of tables with the frequency of each season-specific detection history. |
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. |
n.species |
the number of species in the data set. |
missing.seasons |
logical vector indicating whether data were
collected or not during a given season (primary period), where
|
For objects of classes unmarkedFitOccuMulti and
unmarkedFrameOccuMulti, detHist returns a list with the
following components:
hist.table.full |
a table with the frequency of each observed detection history. The species are coded with letters and follow the same order of presentation as in the other parts of the output. |
hist.table.species |
a list of tables with the frequency of
each species-specific detection history. The last element of
|
out.freqs |
a matrix where the rows correspond to each species
and where columns consist of the number of sites sampled during the
season ( |
out.props |
a matrix where the rows correspond to each species
and where columns consist of the proportion of sites with at least
one detection during the season ( |
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. |
n.species |
the number of species 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
MacKenzie, D. I., Nichols, J. D., Lachman, G. B., Droege, S., Royle, J. A., Langtimm, C. A. (2002) Estimating site occupancy rates when detection probabilities are less than one. Ecology 83, 2248–2255.
MacKenzie, D. I., Nichols, J. D., Hines, J. E., Knutson, M. G., Franklin, A. B. (2003) Estimating site occupancy, colonization, and local extinction when a species is detected imperfectly. Ecology 84, 2200–2207.
MacKenzie, D. I., Nichols, J. D., Seamans, M. E., Gutierrez, R. J. (2009) Modeling species occurrence dynamics with multiple states and imperfect detection. Ecology 90, 823–835.
Mazerolle, M. J. (2015) Estimating detectability and biological parameters of interest with the use of the R environment. Journal of Herpetology 49, 541–559.
Miller, D. A. W., Nichols, J. D., McClintock, B. T., Campbell Grant, E. H., Bailey, L. L. (2011) Improving occupancy estimation when two types of observational error occur: non-detection and species misidentification. Ecology 92, 1422–1428.
Nichols, J. D., Hines, J. E., Mackenzie, D. I., Seamans, M. E., Gutierrez, R. J. (2007) Occupancy estimation and modeling with multiple states and state uncertainty. Ecology 88, 1395–1400.
Rota, C. T., Ferreira, M. A. R., Kays, R. W., Forrester, T. D., Kalies, E. L., McShea, W. J., Parsons, A. W., Millspaugh, J. J. (2016) A multispecies occupancy model for two or more interacting species. Methods in Ecology and Evolution 7, 1164–1173.
Royle, J. A., Link, W. A. (2006) Generalized site occupancy models allowing for false positive and false negative errors. Ecology 87, 835–841.
Royle, J. A., Nichols, J. D. (2003) Estimating abundance from repeated presence-absence data or point counts. Ecology 84, 777–790.
See Also
covDiag, countHist, countDist,
detTime, mb.chisq, mb.gof.test
Examples
##data from Mazerolle (2015)
## Not run:
data(bullfrog)
##detection data
detections <- bullfrog[, 3:9]
##load unmarked package
if(require(unmarked)){
##assemble in unmarkedFrameOccu
bfrog <- unmarkedFrameOccu(y = detections)
##compute descriptive stats from data object
detHist(bfrog)
##run model
fm <- occu(~ 1 ~ 1, data = bfrog)
##compute descriptive stats from model object
detHist(fm)
}
## End(Not run)