simhmltm.w: Simulate line transect survey data using availability time...

In david-borchers/hmltm: Line transect estimation with hidden Markov availability models

Simulate line transect survey data using availability time series.

Description

Simulates line transect survey data in which animal availability is simulated by sampling from time series of availability data (from tagged animals, for example). Currently only for models with no covariates.

Usage

simhmltm.w(
  adat,
  xmax,
  ymax,
  spd,
  animals,
  hfun,
  pars,
  N,
  dmax = NULL,
  seed = NULL,
  poiss = FALSE
)

Arguments

adat	list of m>=1 vectors containing availability binary time series or depths time series.
xmax	maximum perpendicular distance to simulate.
ymax	maximum forward distance to simulate (must be at or beyond point that detection hazard function is effectively zero).
spd	speed observer is moving.
animals	a vector of up to m integers specifying which members of the list adat are to be used to simulate availability. (e.g. animals=c(1,3,5) says the first, third and fifth time series in adat are to be used).
hfun	detection hazard function name.
pars	detection hazard function parameters.
N	number of animals within distance xmax of the transect line and hence subject to being detected (or possibly not).
dmax	if not NULL, then it is the depth above which animals are considered to be available, and adat is taken to be time series of depths, i.e. all adat[[i]]<=dmax are taken as times animals are available. If dmax is NULL, then adat must be binary and all 1's are taken as times animals are available.
seed	random number seed.
poiss	if TRUE, the availability time series are randomly permuted, hence generating the equivalent of a Poisson availability process.

Details

Simulates (x,y) observations from a population of N animals using detection hazard specified by hfun & pars, and resampling from the availability time series in adat for animal availability. Survey parameters are in survey.pars.

Value

Data frame with two elements: $x and $y, being perpendicular and forward distances of detected animals, respectively.

david-borchers/hmltm documentation built on Oct. 29, 2023, 9:07 p.m.