View source: R/detection_probability_functions.R
estgGenericSize | R Documentation |
Generic g estimation for a combination of SE model and CP model under a given search schedule
The g estimated by estgGenericSize
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.
estgGenericSize(
days,
modelSetSize_SE,
modelSetSize_CP,
modelSizeSelections_SE,
modelSizeSelections_CP,
nsim = 1000
)
days |
Search schedule data as a vector of days searched |
modelSetSize_SE |
Searcher Efficiency model set for multiple sizes |
modelSetSize_CP |
Carcass Persistence model set for multiple sizes |
modelSizeSelections_SE |
vector of SE models to use, one for each
size. Size names are required, and names must match those of
modelSetSize_SE. E.g.,
|
modelSizeSelections_CP |
vector of CP models to use, one for each size |
nsim |
the number of simulation draws |
list of g estimates, with one element in the list corresponding to each of the cells from the cross-model combination
data(mock)
pkmModsSize <- pkm(formula_p = p ~ HabitatType,
formula_k = k ~ HabitatType, data = mock$SE,
obsCol = c("Search1", "Search2", "Search3", "Search4"),
sizeCol = "Size", allCombos = TRUE)
cpmModsSize <- cpm(formula_l = l ~ Visibility,
formula_s = s ~ Visibility, data = mock$CP,
left = "LastPresentDecimalDays",
right = "FirstAbsentDecimalDays",
dist = c("exponential", "lognormal"),
sizeCol = "Size", allCombos = TRUE)
pkMods <- c("S" = "p ~ 1; k ~ 1", "L" = "p ~ 1; k ~ 1",
"M" = "p ~ 1; k ~ 1", "XL" = "p ~ 1; k ~ 1"
)
cpMods <- c("S" = "dist: exponential; l ~ 1; NULL",
"L" = "dist: exponential; l ~ 1; NULL",
"M" = "dist: exponential; l ~ 1; NULL",
"XL" = "dist: exponential; l ~ 1; NULL"
)
avgSS <- averageSS(mock$SS)
gsGeneric <- estgGenericSize(nsim = 1000, days = avgSS,
modelSetSize_SE = pkmModsSize,
modelSetSize_CP = cpmModsSize,
modelSizeSelections_SE = pkMods,
modelSizeSelections_CP = cpMods
)
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