sim.linearpopn {secrlinear} | R Documentation |
Simulate Animals on Lines
Description
This function is a simple substitute for the secr function
sim.popn()
for the case of a linear habitat.
Usage
sim.linearpopn(mask, D, N, Ndist = c('poisson', 'fixed'), ...)
Arguments
mask |
linearmask object |
D |
numeric density animals / km |
N |
number of individuals |
Ndist |
character string for distribution of total number of individuals |
... |
other arguments passed to |
Details
The linearmask input represents a discretized line - essentially a chain
of line segments. By default, each segment is populated with a Poisson number of
individuals. The user may specify D
or N
.
D
may be a vector with one density per mask pixel, or a single
number that will be applied across all pixels.
If Ndist = 'fixed'
then a constant number of individuals N are
simulated in each trial; otherwise N has a Poisson distribution across
trials. N = sum(D
) x mask length if D
is
specified.
This is a simplified wrapper for sim.popn
called
with model2D = "linear"
.
Value
Object of class c(‘linearpopn’, ‘popn’, ‘data.frame’).
Note
The population output from sim.linearpopn
may be used unchanged
with secr functions such as
sim.capthist
. However, to be faithful to the
linear network you should set the ‘userdist’ argument of
sim.capthist
to networkdistance
.
See Also
Examples
x <- seq(0, 4*pi, length = 200)
xy <- data.frame(x = x*100, y = sin(x)*300)
mask <- read.linearmask(data = xy, spacing = 10)
trps <- make.line(mask, n = 15, startbuffer = 1000, by = 30)
newmask <- clipmask(mask, trps, buffer = 200)
linpop <- sim.linearpopn(newmask, 200)
CH <- sim.capthist(trps, linpop, userdist = networkdistance)
plot(newmask)
plot(CH, add = TRUE)
secr.fit(CH, mask = mask, details = list(userdist = networkdistance))