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sim

simulate animal tracks

Description

simulate from the rw, crw of mpm process models to generate a set of x,y (or lon,lat) coordinates with or without error from supplied input parameters.

Usage

sim(
  N = 100,
  start = list(c(0, 0), as.POSIXct(format(Sys.time(), tz = "UTC", usetz = TRUE))),
  model = c("rw", "crw", "mpm"),
  vmax = 4,
  sigma = c(4, 4),
  rho_p = 0,
  D = 0.05,
  sigma_g = 1.25,
  error = c("ls", "kf"),
  tau = c(1.5, 0.75),
  rho_o = 0,
  tdist = c("reg", "gamma"),
  ts = 3,
  tpar = c(0.23, 1),
  alpha = c(0.9, 0.8)
)

Arguments

`N`	number of time steps to simulate
`start`	coordinates and datetime of start location for simulated track
`model`	simulate from the `rw`, `crw` or `mpm` process models
`vmax`	maximum travel rate (m/s) of simulated animal
`sigma`	a vector of process error sd's for the `rw` model (ignored if `model != "rw"`)
`rho_p`	correlation parameter for `rw` model process covariance matrix (ignored if `model != "rw"`)
`D`	diffusion coefficient for `crw` model process covariance matrix (ignored if `model != "crw"`)
`sigma_g`	random walk sd for time-varying move persistence parameter (ignored if `model != "mpm"`)
`error`	indicates whether measurement error should mimic Argos Least-Squares ("ls") or Argos Kalman Filter ("kf")
`tau`	vector of LS measurement error sd's (ignored if `error = "kf"`)
`rho_o`	correlation parameter for LS covariance matrix (ignored if `error = "kf"`)
`tdist`	distribution for simulating location times ("reg" generates locations at regular ts intervals, in h; "gamma" uses a gamma distribution to generate random time intervals)
`ts`	time interval in h (ignored if `tdist = "gamma"`)
`tpar`	shape and scale parameters for the gamma distributed times (ignored if `tdist = "reg"`)
`alpha`	transition probabilities switching model versions of `rw` or `crw` models. Probabilities are the transition matrix diagonals (ignored if sigma has length 2 or D has length 1)

Value

a tibble is returned with columns that can include some or all of the following, depending on the arguments used

`date`	time as POSIXct tz = UTC (default)
`lc`	Argos location class
`lon`	longitude with error
`lat`	latitude with error
`x`	x in km from arbitrary origin without error
`y`	y in km from arbitrary origin without error
`x.err`	a random deviate drawn from Argos LS or KF error distribution
`y.err`	a random deviate drawn from Argos LS or KF error distribution
`smaj`	Argos error ellipse semi-major axis in m (if error = "kf")
`smin`	Argos error ellipse semi-minor axis in m (if error = "kf")
`eor`	Argos error ellipse orientation in degrees (if error = "kf")
`u`	velocity in x direction (if model = "crw")
`v`	velocity in y direction (if model = "crw")
`b`	behavioural state (if model = "rw" or "crw" and multiple process variances given, see examples)
`g`	movement persistence - the autocorrelation between successive movements on the interval 0,1 (if model = "mpm")

Examples

tr <- sim(N = 200, model = "crw", D = 0.1, error = "kf", tdist = "reg", ts=12)
plot(tr, error = TRUE)

tr <- sim(N = 200, model = "rw", sigma = c(4,4,0.5,0.5), error = "ls", tdist = "reg")
plot(tr)

tr <- sim(N = 200, model = "crw", D = c(0.1, 0.05), error = "kf", tdist="reg")
plot(tr)

tr <- sim(N = 200, model = "mpm", sigma_g = 1.2, error = "ls", tau = c(2, 1.5), 
tdist = "gamma", tpar = c(1, 4))
plot(tr, error = TRUE, pal = "Cividis")

foieGras

Fit Continuous-Time State-Space and Latent Variable Models for Quality Control of Argos Satellite (and Other) Telemetry Data and for Estimating Movement Behaviour

v0.7-6

MIT + file LICENSE

Authors

Ian Jonsen [aut, cre, cph], Toby Patterson [aut, ctb]

Initial release

2021-04-26

sim