esa.plot  R Documentation 
Plot effective sampling area (Borchers and Efford 2008) as a function of increasing buffer width.
esa.plot (object, max.buffer = NULL, spacing = NULL, max.mask = NULL,
detectfn, detectpar, noccasions, binomN = NULL, thin = 0.1,
poly = NULL, poly.habitat = TRUE, session = 1, plt = TRUE,
type = c('density', 'esa', 'meanpdot', 'CVpdot'), n = 1, add = FALSE,
overlay = TRUE, conditional = FALSE, ...)
object 

max.buffer 
maximum width of buffer in metres 
spacing 
distance between mask points 
max.mask 

detectfn 
integer code or character string for shape of detection function 0 = halfnormal etc. – see detectfn 
detectpar 
list of values for named parameters of detection function 
noccasions 
number of sampling occasions 
binomN 
integer code for discrete distribution (see

thin 
proportion of mask points to retain in plot and output 
poly 
matrix of two columns interpreted as the x and y coordinates of a bounding polygon (optional) 
poly.habitat 
logical as in 
session 
vector of session indices (used if 
plt 
logical to plot results 
type 
character, what to plot 
n 
integer number of distinct individuals detected 
add 
logical to add line to an existing plot 
overlay 
logical; if TRUE then automatically 
conditional 
logical; if TRUE the reported mean and CV are conditional on detection
(see 
... 
graphical arguments passed to plot() and lines() 
Effective sampling area (esa) is defined as the integral of net
capture probability (p.(\mathbf{X})
) over a
region. esa.plot
shows the effect of increasing region size on
the value of esa for fixed values of the detection parameters. The
max.buffer
or max.mask
arguments establish the maximum
extent of the region; points (cells) within this mask are sorted by
their distance d_k
from the nearest detector. esa(buffer) is
defined as the cumulative sum of cp.(\mathbf{X})
for
d_k(\mathbf{X}) <= \mbox{buffer}
, where c
is the area associated with each cell.
The default (type = 'density'
) is to plot the reciprocal of esa
multiplied by n
; this is on a more familiar scale (the density
scale) and hence is easier to interpret.
Because esa.plot
uses the criterion 'distance to nearest
detector', max.mask
should be constructed to include all
habitable cells within the desired maximum buffer and no others. This
is achieved with type = "trapbuffer"
in make.mask
. It is
a good idea to set the spacing
argument of make.mask
rather than relying on the default based on nx
. Spacing may be
small (e.g. sigma/10) and the buffer of max.mask
may be quite
large (e.g. 10 sigma), as computation is fast.
Thinning serves to reduce redundancy in the plotted points, and (if
the result is saved and printed) to generate more legible numerical
output. Use thin=1
to include all points.
esa.plot
calls the internal function esa.plot.secr
when
object
is a fitted model. In this case detectfn
,
detectpar
and noccasions
are inferred from
object
.
A dataframe with columns
buffer 
buffer width 
esa 
computed effective sampling area 
density 
n/esa 
pdot 

pdotmin 
cumulative minimum ( 
meanpdot 
expected pdot across mask (see 
CVpdot 
CV of pdot across mask (see 
If plt = TRUE
the dataframe is returned invisibly.
The response of effective sampling area to buffer width is just one
possible mask diagnostic; it's fast, graphic, and often
sufficient. mask.check
performs more intensive checks,
usually for a smaller number of buffer widths.
The old argument 'as.density' was superceded by 'type' in 3.1.7.
Borchers, D. L. and Efford, M. G. (2008) Spatially explicit maximum likelihood methods for capture–recapture studies. Biometrics 64, 377–385.
mask
, pdot
, CVpdot
,
make.mask
, mask.check
,
Detection functions
## Not run:
## with previously fitted model
esa.plot(secrdemo.0)
## from scratch
trps < make.grid()
msk < make.mask(trps, buffer = 200, spacing = 5, type = "trapbuffer")
detectpar < list(g0 = 0.2, sigma = 25)
esa.plot(trps,,, msk, 0, detectpar, nocc = 10, col = "blue")
esa.plot(trps,,, msk, 0, detectpar, nocc = 5, col = "green",
add = TRUE)
esa.plot(trps,,, msk, 0, detectpar, nocc = 5, thin = 0.002, plt = FALSE)
## End(Not run)
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