dosim: Simulates 2-plane data & fits LCE and CCR models to this
In david-borchers/LCE_paper: Latent Capture History estimation package

Simulates 2-plane data & fits LCE and CCR models to this

dosim(
  D.2D,
  L,
  w,
  b,
  sigmarate,
  k,
  planespd,
  kappa,
  tau,
  p = c(1, 1),
  movement = list(forward = TRUE, sideways = TRUE),
  fix.N = TRUE,
  En = NULL,
  Nsim = 100,
  writeout = TRUE,
  seed = 1,
  simethod = "MLE",
  control.opt = control.opt,
  hessian = TRUE,
  adj.mvt = FALSE,
  ft.normal = FALSE,
  sim.ft.normal = FALSE,
  progbar = TRUE,
  fn.append = NULL
)

`D.2D`	animal density (number per sq km)
`L`	transect length (km)
`w`	searched strip width (km)
`b`	buffered strip width (km)
`sigmarate`	the Brownian movement rate (sigma) parameter
`k`	the lag between observers (seconds)
`planespd`	Observer speed in km/sec
`kappa`	mean time animals on surface (seconds)
`tau`	mean dive cycle leength (seconds)
`p`	vector of each observers' detection prob for available animals
`movement`	list with components `forward` and `sideways`, which should be TRUE or FALSE depending on what sort of movement you want to simulate with. Note: Estimation does not currently work when simulating with `forward=FALSE`.
`fix.N`	Boolean variable, which if TRUE simulates with the same abundance, equal to the expected, abundance, each simulation rep.
`En`	Ignored if NULL, else the expected number of detections by each observer. Function sets transect length, `L`, to achieve this
`Nsim`	Number of simulations to do
`writeout`	Boolean, which if TRUE, causes results to be written to file and the name of the file (which encodes the simulation parameters) to be returned invisibly.
`seed`	Integer seed which can be used for repoducible results
`control.opt`	passed to `optim`
`hessian`	Boolean controlling whether or not to return Hessian (and interval estimates for MLE method).
`adj.mvt`	If TRUE, MLE method takes account of randomness in lag between encounters; if FALSE, it sets these all to the lag, `k`.
`ft.normal`	if TRUE, approximates Brownian motion hitting time with a normal distribution when estimation with MLE method, else uses exact expression for Brownian hitting time
`sim.ft.normal`	if TRUE, approximates Brownian motion hitting time with a normal distribution when simulating, else uses exact expression for Brownian hitting time in simulation. NOTE: Exact simulator seems to have too low variance; with fast observers relative to animals, normal approx is very good (see function `dft` and code in file `ft_plot.R`).
`progbar`	If TRUE, puts a progress bar on screen so you can monitor simulation progress.
`fn.append`	A text string to append to the default output file name.
`simthod`	Character; either 'MLE' (for max likelihood simulator) or 'Palm' for CCR simulator from package `palm`.