The `make.scenarios`

function requires prior knowledge of
population density and the intercept of the detection function
(g0). This function provides an alternative mechanism for generating
scenarios from a value of sigma and target values for the numbers of
individuals n and recaptures r. Only a halfnormal detection function
is supported (probability, not hazard), and many options in
`make.scenarios`

have yet to be implemented. Only a single
detector layout and single mask may be specified.

1 2 | ```
scenariosFromStatistics(sigma, noccasions, traps, mask, nval, rval,
g0.int = c(0.001, 0.999))
``` |

`sigma` |
numeric vector of one or more values for sigma |

`noccasions` |
integer vector of number of sampling occasions |

`traps` |
traps object |

`mask` |
mask object |

`nval` |
integer vector of values of n |

`rval` |
integer vector of values of r |

`g0.int` |
numeric vector defining the interval to be searched for g0 |

The algorithm is based on R code in Appendix B of Efford, Dawson and Borchers (2009).

A scenario dataframe with one row for each combination of `sigma`

,
`noccasions`

, `nval`

and `rval`

.

Efford, M. G., Dawson, D. K. and Borchers, D. L. (2009) Population
density estimated from locations of individuals on a passive detector
array. *Ecology* **90**, 2676–2682.

1 2 3 4 5 6 | ```
grid36 <- make.grid(nx = 6, ny = 6, spacing = 200)
mask <- make.mask(grid36, buffer = 2000)
scen <- scenariosFromStatistics (sigma = c(200,400), noccasions = 44,
traps = grid36, mask = mask, nval = 14, rval = 34)
sim <- run.scenarios(scen, nrepl = 5, traps = grid36, mask = mask)
summary(sim)
``` |

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