openCR (version 2.2.6)

moving.fit: Moving Window Functions

Description

Apply a function to successive multi-session windows from a capthist object. The default function is openCR.fit, but any function may be used whose first argument accepts a capthist object.

Usage

moving.fit (..., width = 3, centres = NULL, filestem = NULL, 
    trace = FALSE, FUN = openCR.fit)
extractFocal (ocrlist, ...)

Value

A list in which each component is the output from FUN applied to one subset. The window width is saved as attribute `width'.

Arguments

...

named arguments passed to openCR.fit (see Details)

width

integer; moving window width (number of primary sessions)

centres

integer; central sessions of windows to consider

filestem

character or NULL; stem used to form filenames for optional intermediate output

trace

logical; if TRUE a status message is given at each call of FUN

FUN

function to be applied to successive capthist objects

ocrlist

openCRlist object returned by moving.fit when FUN = openCR.fit

Details

moving.fit applies FUN to successive multi-session subsets of the data in the capthist argument. width should be an odd integer. centres may be used to restrict the range of windows considered; the default is to use all complete windows (width%/%2 + 1)...).

If a filestem is specified then each result is output to a file that may be loaded with load. This is useful if fitting takes a long time and analyses may be terminated before completion.

extractFocal returns the focal-session (central) estimates from a moving.fit with FUN = openCR.fit. The ... argument is passed to predict.openCR; it may be used, for example, to choose a different alpha level for confidence intervals.

extractFocal is untested for complex models (e.g. finite mixtures).

See Also

openCR.fit

Examples

## number of individuals detected
moving.fit(capthist = OVpossumCH, FUN = nrow)

if (FALSE) {

## if package R2ucare installed
if (requireNamespace("R2ucare"))
    moving.fit(capthist = OVpossumCH, FUN = ucare.cjs, width = 5, tests = "overall_CJS")

## using default FUN = openCR.fit

mf1 <- moving.fit(capthist = OVpossumCH, type = 'JSSAfCL', 
     model = list(p~t, phi~t))
lapply(mf1, predict)
extractFocal(mf1)
     
msk <- make.mask(traps(OVpossumCH[[1]]), nx = 32)
mf2 <- moving.fit(capthist = OVpossumCH, mask = msk, type = 'JSSAsecrfCL')
extractFocal(mf2)

}