Description Usage Arguments Value Author(s) References See Also Examples
View source: R/multimark_functions.R
This function generates an object of class multimarkSCRsetup
that is required to fit spatial ‘multimark’ models.
1 2 3  processdataSCR(Enc.Mat, trapCoords, studyArea = NULL, buffer = NULL,
ncells = NULL, data.type = "never", covs = data.frame(),
known = integer(), scalemax = 10)

Enc.Mat 
A matrix containing the observed encounter histories with rows corresponding to individuals and ( 
trapCoords 
A matrix of dimension 
studyArea 
is a 3column matrix containing the coordinates for the centroids of a contiguous grid of cells that define the study area and available habitat. Each row corresponds to a grid cell. The first 2 columns indicate the Cartesian x and ycoordinate for the centroid of each grid cell, and the third column indicates whether the cell is available habitat (=1) or not (=0). All cells must be square and have the same resolution. If 
buffer 
A scaler in same units as 
ncells 
The number of grid cells in the study area when 
data.type 
Specifies the encounter history data type. All data types include nondetections (type 0 encounter), type 1 encounter (e.g., leftside), and type 2 encounters (e.g., rightside). When both type 1 and type 2 encounters occur for the same individual within a sampling occasion, these can either be "nonsimultaneous" (type 3 encounter) or "simultaneous" (type 4 encounter). Three data types are currently permitted:

covs 
A data frame of time and/or trapdependent covariates for detection probabilities (ignored unless 
known 
Optional integer vector indicating whether the encounter history of an individual is known with certainty (i.e., the observed encounter history is the true encounter history). Encounter histories with at least one type 4 encounter are automatically assumed to be known, and 
scalemax 
Upper bound for internal rescaling of grid cell centroid coordinates. Default is 
An object of class multimarkSCRsetup
.
Brett T. McClintock
Bonner, S. J., and Holmberg J. 2013. Markrecapture with multiple, noninvasive marks. Biometrics 69: 766775.
Gopalaswamy, A.M., Royle, J.A., Hines, J.E., Singh, P., Jathanna, D., Kumar, N. and Karanth, K.U. 2012. Program SPACECAP: software for estimating animal density using spatially explicit capturerecapture models. Methods in Ecology and Evolution 3:10671072.
McClintock, B. T., Conn, P. B., Alonso, R. S., and Crooks, K. R. 2013. Integrated modeling of bilateral photoidentification data in markrecapture analyses. Ecology 94: 14641471.
Royle, J.A., Karanth, K.U., Gopalaswamy, A.M. and Kumar, N.S. 2009. Bayesian inference in camera trapping studies for a class of spatial capturerecapture models. Ecology 90: 32333244.
multimarkSCRsetupclass
, multimarkClosedSCR
1 2 3 4 5 6 7 8 9 10 11 12  # This example is excluded from testing to reduce package check time
# Example uses unrealistically low values for nchain, iter, and burnin
#Generate object of class "multimarksetup" from simulated data
sim.data<simdataClosedSCR()
Enc.Mat < sim.data$Enc.Mat
trapCoords < sim.data$spatialInputs$trapCoords
studyArea < sim.data$spatialInputs$studyArea
setup < processdataSCR(Enc.Mat,trapCoords,studyArea)
#Run single chain using the default model for simulated data
example.dot<multimarkClosedSCR(mms=setup)

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