Learn R Programming

secr (version 3.0.1)

snip: Slice Transect Into Shorter Sections

Description

This function splits the transects in a `transect' or `transectX' traps object into multiple shorter sections. The function may also be applied directly to a capthist object based on transect data. This makes it easy to convert detection data collected along linear transects to point detection data (see Example).

Usage

snip(object, from = 0, by = 1000, length.out = NULL, keep.incomplete = TRUE)

Arguments

object
secr `traps' or `capthist' object based on transects
from
numeric starting posiiton (m)
by
numeric length of new transects (m)
length.out
numeric number of new transects, as alternative to `by'
keep.incomplete
logical; if TRUE then initial or terminal sections of each original transect that are less than `by' will be retained in the output

Value

A `traps' or `capthist' object, according to the input. If keep.incomplete == FALSE animals and detections from the

Details

If a positive length.out is specified, by will be computed as (transectlength(object) - from) / length.out.

See Also

transectlength, discretize

Examples

Run this code

x <- seq(0, 4*pi, length = 41)
temptrans <- make.transect(x = x*100, y = sin(x)*300)
plot (snip(temptrans, by = 200), markvertices = 1)

## Not run: ------------------------------------
# 
# ## simulate some captures
# tempcapt <- sim.capthist(temptrans, popn = list(D = 2,
#    buffer = 300), detectpar = list(g0 = 0.5, sigma = 50),
#    binomN = 0)
# 
# ## snip capture histories
# tempCH <- snip(tempcapt, by = 20)
# 
# ## collapse from 'transect' to 'count', discarding location within transects
# tempCH <- reduce(tempCH, outputdetector = "count")
# 
# ## fit secr model and examine H-T estimates of density
# derived(secr.fit(tempCH, buffer = 300, CL = TRUE, trace = FALSE))
# 
# ## also, may split an existing transect into equal lengths
# ## same result:
# plot(snip(temptrans, by = transectlength(temptrans)/10),
#     markvertices = 1)
# plot(snip(temptrans, length.out = 10), markvertices = 1)
# 
## ---------------------------------------------

Run the code above in your browser using DataLab