Plot CDF, PDF, or rcd (relative carcass density) for a single
carcass dispersion glm model (dd object) or a list of
models (ddArray object).
# S3 method for ddArray
plot(
x,
type = "CDF",
extent = "full",
distr = "all",
xmax = NULL,
resolution = 250,
mod_highlight = NULL,
...
)# S3 method for dd
plot(
x,
type = "CDF",
extent = "full",
xmax = NULL,
resolution = 250,
nsim = 1000,
CL = 0.9,
...
)
# S3 method for fmod
plot(x, ...)
# S3 method for polygonLayout
plot(x, ...)
# S3 method for layoutSimple
plot(x, ...)
# S3 method for psiHat
plot(x, ...)
# S3 method for dwphat
plot(x, ...)
Plot displayed; no return value.
model(s) to plot
Type or representation of carcass dispersion to plot:
"CDF", "PDF", or "rcd". The "CDF" gives the
fraction of carcasses falling within r meters from a turbine and
"PDF" is the associated probability density. The "rcd" gives the
relative carcass density at a point r meters from a turbine and is
PDF/(2 * pi * r).
Plot dispersions as fraction of total carcasses ("full")
or as fraction of carcasses within the searched area ("win").
vector of names of distributions to plot or set = "all"
maximum distance to show in the graph; if xmax = NULL, the
maximum distance is taken as the max distance in the data set to which the
models were fit.
The number of line segments to break the curves into when
plotting (i.e., x = seq(0, xmax, length.out = resolution)). Higher
resolutions give smoother-looking curves.
Character string giving the name of the model to
highlight by plotting it last and with lwd = 2. If NULL, the
curve associated with the lowest (best) AICc score is highlighted.
arguments that may be passed to plotting functions
Number of simulation reps to use for estimating confidence bounds
for dd plot (ignored for ddArray
objects)
confidence level to show in a dd plot (ignored
for ddArray objects)
ddArray objects are plotted with lines in order
of decreasing AICc, so that the "better" models are closer to the top and
more prominent. The model with the lowest AICc ("best" model) is plotted
last with a heavier line than the others.
For dd objects, the curve for the MLE of the parameters
is plotted, along with a 100CL% confidence bounds determined for
nsim simulation reps
The legend follows the ordering given by modelFilter with
the default sieve or, if extent = "win" by (1) delta AICc < 10,
(2) the absence of high-influence points, and (2) AICc. The best model
according to the filter is listed first, with a heavier line than the others;
the remaining distributions are listed in descending order, with the best
models in the leftmost column.