Trend | R Documentation |
Functions for multi-session density trend analysis.
predictDlambda(object, alpha = 0.05)
object |
multi-session secr object output from secr.fit |
alpha |
alpha level for confidence intervals |
Usage is described in secr-trend.pdf. Briefly, setting details argument 'Dlambda' in 'secr.fit
causes the density model (D~xxx) to be interpreted as a session-specific trend model with parameters for the initial density (D1) and each subsequent session-on-session change in density \lambda[t] = D[t+1]/D[t]
.
A table of session-specific estimates (initial D, subsequent \lambda[t]
) with SE and confidence intervals.
predictDsurface
,
secr.fit
# a model with constant lambda
msk <- make.mask(traps(ovenCH[[1]]), buffer = 300, nx = 25)
fit <- secr.fit(ovenCH, model = D~1, mask = msk, trace = FALSE,
details = list(Dlambda = TRUE), ncores = 2)
predictDlambda(fit)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.