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

In b-steve/sscr: Spatial correlation structures for detections of individuals in spatial capture-recapture models

Description

Simulates SSCR data.

Usage

sim.sscr(
  fit = NULL,
  traps,
  mask,
  D,
  resp = NULL,
  resp.pars = NULL,
  detfn = "hhn",
  cov.structure = "none",
  re.multiplier = "er",
  det.pars = NULL,
  cov.pars = NULL,
  toa.pars = NULL,
  trunc.acs = TRUE,
  keep.acs = FALSE,
  mask.spacing = NULL
)

Arguments

fit	A fitted model object returned by fit.sscr(). If provided, simulation is based on this fitted model, and all other arguments are ignored.
traps	A matrix with two columns, providing the Cartesian coordinates of the detector locations.
mask	A mask object for integration over the survey area.
D	Animal density (individuals per hectare).
resp	Response distribution for capture history elements. Either "binom" for a binomial distribution, "pois" for a Poisson distribution, "nb" for a negative binomial distribution, "nba" for a negative binomial–alpha distribution, or "cmp" for a Conway-Maxwell-Poisson distribution.
resp.pars	A named vector of additional parameters for the response distribution. If resp is "binom", then this should have a single element named giving the fixed number of trials. If resp is "cmp", then this should have a single element for the start value of the estimated parameter nu (see rcmp). If resp is "nb", then this should have a single element for the start value of the estimated parameter size (see rnbinom).
detfn	Detection function, given by a character string. Use "hn", for halfnormal, "hhn" for hazard halfnormal, and "hr" for hazard rate.
cov.structure	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.
re.multiplier	A character string specifying how the expected encounter rate is calculated from the random effect. This is either (1) "er" for multiplication by the baseline encounter rate, or (2) "prob" for multiplication by the baseline encounter probability.
det.pars	List of detection function parameters.
cov.pars	List of covariance parameters.
toa.pars	List of time-of-arrival parameters.
trunc.acs	Logical. If TRUE, activity centres are truncated to the region covered by the mask.
keep.acs	Logical. If TRUE, activity centre locations are returned along with the captures histories.
mask.spacing	Optional. The distance between adjacent mask points. Providing a value will save processing time if activity centres are being truncated to the mask region.

b-steve/sscr documentation built on May 30, 2021, 1:23 a.m.