Plot {dwp}

Plot dd and ddArray Objects

Description

Plot CDF, PDF, or rcd (relative carcass density) for a single carcass dispersion glm model (dd object) or a list of models (ddArray object).

Usage

## S3 method for class 'ddArray'
plot(
  x,
  type = "CDF",
  extent = "full",
  distr = "all",
  xmax = NULL,
  resolution = 250,
  mod_highlight = NULL,
  ...
)

## S3 method for class 'dd'
plot(
  x,
  type = "CDF",
  extent = "full",
  xmax = NULL,
  resolution = 250,
  nsim = 1000,
  CL = 0.9,
  ...
)

## S3 method for class 'fmod'
plot(x, ...)

## S3 method for class 'polygonLayout'
plot(x, ...)

## S3 method for class 'layoutSimple'
plot(x, ...)

## S3 method for class 'psiHat'
plot(x, ...)

## S3 method for class 'dwphat'
plot(x, ...)

Arguments

x

model(s) to plot

type

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).

extent

Plot dispersions as fraction of total carcasses ("full") or as fraction of carcasses within the searched area ("win").

distr

vector of names of distributions to plot or set = "all"

xmax

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.

resolution

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.

mod_highlight

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

nsim

Number of simulation reps to use for estimating confidence bounds for dd plot (ignored for ddArray objects)

CL

confidence level to show in a dd plot (ignored for ddArray objects)

Details

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.

Value

Plot displayed; no return value.