make.scenarios: Construct Scenario Data Frame

In secrdesign: Sampling Design for Spatially Explicit Capture-Recapture

Construct Scenario Data Frame

Description

This function prepares a dataframe in which each row specifies a simulation scenario. The dataframe is used as input to run.scenarios.

Usage

make.scenarios(trapsindex = 1, noccasions = 3,  nrepeats = 1, 
  D, g0, sigma, lambda0, epsilon, tau, z,
  detectfn = 0, recapfactor = 1, popindex = 1, detindex = 1, fitindex = 1, 
  groups, crosstraps = TRUE)

Arguments

trapsindex	integer vector determining the traps object to use
noccasions	integer vector for the number of sampling occasions
nrepeats	integer vector of multipliers for D (see Details)
D	numeric vector of values for the density parameter (animals / hectare)
g0	numeric vector of values for the g0 parameter
sigma	numeric vector of values for the sigma parameter (m)
lambda0	numeric vector of values for the lambda0 parameter
epsilon	numeric vector of values for the epsilon parameter (m)
tau	numeric vector of values for the tau parameter (OU correlation)
z	numeric vector of values for the z parameter
detectfn	vector of valid detection function codes (numeric or character)
recapfactor	numeric vector of values for recapfactor (sim.capthist)
popindex	integer vector determining which population model is used
detindex	integer vector determining which detection options are used
fitindex	integer vector determining which model is fitted
groups	character vector of group labels (optional)
crosstraps	logical; if TRUE the output includes all combinations of trapsindex, noccasions and nrepeats

Details

The index in trapsindex is used in run.scenarios to select particular detector arrays from the list of arrays provided as an argument to that function.

The function generates all combinations of the given parameter values using expand.grid. By default, it also generates all combinations of the parameters with trapsindex and the number of sampling occasions. If crosstraps is FALSE then trapsindex, noccasions, and nrepeats are merely used to fill in these columns in the output dataframe.

Use the detection parameters (g0, sigma, lambda0, epsilon, tau, z) that apply for the chosen detection function (detectfn). Others will be ignored.

Detectfn 20 (Ornstein-Uhlenbeck) is currently available in secrdesign but not in secr (see simOU.capthist). It uses epsilon, sigma and tau (= 1/beta).

Designs may use multiple detector arrays with the same internal geometry (e.g., number and spacing of traps). The number of such arrays is varied with the nrepeats argument. For example, you may compare designs with many small arrays or a few large ones. In practice, run.scenarios simulates a single layout with density D * nrepeats. This shortcut is not appropriate when animals compete for traps (detector = ‘single’).

fitindex allows a choice of different models when the argument fit.args of run.scenarios is a compound list.

If groups is provided each scenario is replicated to the length of groups and a column ‘group’ is added.

Value

Dataframe with one row per scenario (or sub-scenario) and the columns

scenario	a number identifying the scenario
group	(optional)
trapsindex
noccasions
nrepeats
D
...
[parameters appropriate to detectfn]
...
detectfn	see detectfn; always numeric
recapfactor
popindex
detindex
fitindex

An attribute ‘inputs’ is saved for possible use in make.array.

See Also

run.scenarios, scenarioSummary, sim.capthist

Examples

make.scenarios(trapsindex = 1, nrepeats = 1, D = c(5,10), sigma = 25,
g0 = 0.2)

secrdesign documentation built on June 13, 2025, 9:08 a.m.