estgGeneric: Estimate generic g

Description

Generic g estimation by simulation from given SE model and CP models under a specific search schedule.

The g estimated by estgGeneric is a generic aggregate detection probability and represents the probability of detecting a carcass that arrives at a (uniform) random time during the period monitored, for each of the possible cell combinations, given the SE and CP models. This is somethat different from the GenEst estimation of g when the purpose is to estimate total mortality (M), in which case the detection probability varies with carcass arrival interval and is difficult to summarize statistically. The estgGeneric estimate is a useful "big picture" summary of detection probability, but would be difficult to work with for estimating M with precision.

Usage

estgGeneric(days, model_SE, model_CP, nsim = 1000, seed_SE = NULL,
  seed_CP = NULL)

Arguments

days

Search schedule data as a vector of days searched

model_SE

Searcher Efficiency model (pkm object)

model_CP

Carcass Persistence model (cpm object)

nsim

the number of simulation draws

seed_SE

seed for random draws of the SE model

seed_CP

seed for random draws of the CP model

Value

gGeneric object that is a list of [1] a list of g estimates, with one element in the list corresponding to each of the cells from the cross-model combination and [2] a table of predictors and cell names associated with the gs

Examples

Run this code

# NOT RUN {
  data(mock)
  model_SE <- pkm(formula_p = p ~ HabitatType, formula_k = k ~ 1,
                data = mock$SE)
  model_CP <- cpm(formula_l = l ~ Visibility, formula_s = s ~ Visibility, 
                data = mock$CP, left = "LastPresentDecimalDays", 
                right = "FirstAbsentDecimalDays")
  avgSS <- averageSS(mock$SS)
  ghatsGeneric <- estgGeneric(days = avgSS, model_SE = model_SE,
   model_CP = model_CP)

# }

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