sim.sscr: Simulating SCR data with second-order spatial dependence

Description Usage Arguments

View source: R/sim.r


Simulates SSCR data.


sim.sscr(traps, mask, D, resp = NULL, = NULL, detfn = "hn",
  cov.structure = "none", = NULL, = NULL, = NULL)



A matrix with two columns, providing the Cartesian coordinates of the detector locations.


A mask object for integration over the survey area.


Animal density (individuals per hectare).


Response distribution for capture history elements. Either "binom" for a binomial distribution, or "pois" for a Poisson distribution.

A named vector of known, fixed parameters for the response distribution. If resp is "binom", then this must have a single element named "size" giving the fixed number of trials; if this argument is not provided, then the default is 1.


Detection function, given by a character string. Use "hn", for halfnormal, "hhn" for hazard halfnormal, and "hr" for hazard rate.


Covariance structure of the random effects. The current options are (1) "none" for no random effects (regular SCR), (2) "independent", for independent random effects (equivalent to counts of detections being overdispersed), (3) "exponential", for random effects with an exponential covariance structure, (4) "sq_exponential" for random effects with a squared exponential covariance structure, (5) "matern", for random effects with a Matern covariance structure, (5) "individual", for random effects that are restricted to being the same at all traps (equivalent to having an independent random effect on lambda0 for each individual), or (6) "lc_exponential" for a linear combination of exponential covariance functions.

List of detection function parameters.

List of covariance parameters.

List of time-of-arrival parameters.

b-steve/sscr documentation built on Dec. 8, 2018, 9:13 a.m.