simest | R Documentation |
Simulates line transect survey with stochastic animal availability, estimates detection probability and related parameters, and reports bias, variance of estimators. Currently only for models with no covariates.
simest(
simethod = "hmm",
shfun,
spars,
ehfun = shfun,
parstart = spars,
survey.pars,
shmm.pars,
ehmm.pars = shmm.pars,
animal = NULL,
adat = NULL,
control.opt,
control.fit,
nsim = 50,
report.progress = TRUE,
En = 100,
doplots = FALSE,
varest = FALSE,
hmmpars.bs = NULL,
print.n = FALSE,
silent = FALSE,
nx = 100
)
simethod |
either "hmm" (for availability simulation with HMM) or "animals" (for availability simulation by resampling availability or depth dime series). |
shfun |
detection hazard function name for simulation. |
spars |
detection hazard function parameters for simulation. |
ehfun |
detection hazard function name for estimation. |
parstart |
detection hazard function parameter start vallues for estimation. |
survey.pars |
survey parameters, as for |
shmm.pars |
hmm.pars list (as for |
ehmm.pars |
hmm.pars list (as for |
animal |
which animals' availability data to use (only need if simethod="animals"). |
adat |
availability data (only need if simethod="animals"): list of m>=1 vectors containing availability binary time series or depths time series. |
control.opt |
optimization parameters passed to |
control.fit |
fit parameters, as for |
nsim |
number of simulations to do. |
report.progress |
if TRUE, reports progress as does simulations. |
En |
Mean sample size for simulations. |
doplots |
if TRUE does plots of simulaton results. |
varest |
if TRUE, estimates variance (using Hessian matrix). |
hmmpars.bs |
output from |
print.n |
if TRUE, prints sample size for each simulation. |
silent |
parameter of |
nx |
number of perpendicular distances intervals to use in evaluating detection probability, p(x). |
list with these elements:
N: population size.
esw: true effective strip half-width.
p0: true p(0).
p.: true mean detection probability.
meann: mean sample size across simulations.
biasNhat: bias of estimated N.
biaseswhat: bias of estiamted esw.
biasp0hat: bias of estimated p(0).
biasphat: bias of estimated mean detection probability.
biasinvphat: bias of estimated inverse mean detection probability.
n: sample sizes.
parest: parameter estimates from each simulation.
p0hat: p(0) estimates from each simulation.
phat: mean detection probability estimates from each simulation.
invphat: inverse mean detection probability estimates from each simulation.
Nhat: abunance estimates from each simulation.
invpse: estimated standard error of inverse mean detection probability estimates from each simulation (if varest=TRUE).
p0se: estimated standard error of p(0) estimates from each simulation (if varest=TRUE).
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