If simulations have been saved from
run.scenarios as fitted
secr models it is necessary to use one of these functions to extract
estimates for later summarization.
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fitted model simulation output from
other arguments passed to predict, coef, derived or region.N
These functions are used when output from
has been saved as fitted models.
require a full fit (including the mask and design0 objects) whereas a trimmed model
is sufficient for
derived is used to compute the Horvitz-Thompson-like estimate
of density when
secr.fit has been used with
= TRUE; it is roughly equivalent to
region.N predicts the realised number (R.N) or expected number
(E.N) in a masked area. When detector layouts and/or
the masked area will also vary (arbitrarily, depending on the buffer
argument ‘xsigma’) unless a mask is provided by the user; this may be
done either in
run.scenarios or in
An object with class (‘estimatetables’, ‘secrdesign’, ‘list’) with
appropriate outputtype (‘predicted’, ‘coef’, ‘derived’, ‘regionN’;
From secrdesign 2.5.3 the methods described here replace the functions
regionN.SL. This is for compatibility with secr.
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## Not run: scen1 <- make.scenarios(D = c(3,6), sigma = 25, g0 = 0.2) traps1 <- make.grid() ## default 6 x 6 grid of multi-catch traps tmp1 <- run.scenarios(nrepl = 10, trapset = traps1, scenarios = scen1, fit = TRUE, extractfn = trim) tmp2 <- predict(tmp1) tmp3 <- select.stats(tmp2, 'D', c('estimate','RB','RSE')) summary(tmp3) ## for derived and region.N need more than just 'trimmed' secr object ## use argument 'keep' to save mask and design0 usually discarded by trim tmp4 <- run.scenarios(nrepl = 10, trapset = traps1, scenarios = scen1, fit = TRUE, extractfn = trim, keep = c('mask','design0')) summary(derived(tmp4)) ## for region.N we must specify the parameter for which we want statistics ## (default 'D' not relevant) tmp5 <- select.stats(region.N(tmp4), parameter = 'E.N') summary(tmp5) ## End(Not run)
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