Description Usage Arguments Details Value Author(s) References See Also Examples
This function generates encounter histories from spatiallyexplicit capturemarkrecapture data consisting of multiple noninvasive marks.
1 2 3 4 5 
N 
True population size or abundance. 
ntraps 
The number of traps. If 
noccas 
Scaler indicating the number of sampling occasions per trap. 
pbeta 
Complementary loglogscale intercept term for detection probability (p). Must be a scaler or vector of length 
tau 
Additive complementary loglogscale behavioral effect term for recapture probability (c). 
sigma2_scr 
Complementary loglogscale term for effect of distance in the “halfnormal” detection function. Ignored unless 
lambda 
Complementary loglogscale term for effect of distance in the “exponential” detection function. Ignored unless 
delta_1 
Conditional probability of type 1 encounter, given detection. 
delta_2 
Conditional probability of type 2 encounter, given detection. 
alpha 
Conditional probability of simultaneous type 1 and type 2 detection, given both types encountered. Only applies 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:

detection 
Model for detection probability as a function of distance from activity centers. Must be " 
spatialInputs 
A list of length 3 composed of objects named
If 
buffer 
A scaler indicating the buffer around the bounding box of 
ncells 
The number of grid cells in the study area when 
scalemax 
Upper bound for grid cell centroid x and ycoordinates. Default is 
plot 
Logical indicating whether to plot the simulated trap coordinates, study area, and activity centers using 
Please be very careful when specifying your own spatialInputs
; multimarkClosedSCR
and markClosedSCR
do little to verify that these make sense during model fitting.
A list containing the following:
Enc.Mat 
Matrix containing the observed encounter histories with rows corresponding to individuals and ( 
trueEnc.Mat 
Matrix containing the true (latent) encounter histories with rows corresponding to individuals and ( 
spatialInputs 
List of length 2 with objects named

centers 

Brett T. McClintock
Bonner, S. J., and Holmberg J. 2013. Markrecapture with multiple, noninvasive marks. Biometrics 69: 766775.
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.
processdataSCR
, multimarkClosedSCR
, markClosedSCR
1 2  #simulate data for data.type="sometimes" using defaults
data<simdataClosedSCR(data.type="sometimes")

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