Plot fit of detection functions and histograms of data from distance sampling trial observer model

Share:

Description

Plots the fitted detection functions for a distance sampling model and histograms of the distances (for unconditional detection functions) or proportion of observations detected within distance intervals (for conditional detection functions) to compare visually the fitted model and data.

Usage

1
2
3
4
5
6
## S3 method for class 'trial'
plot(x, which = 1:2, breaks = NULL, nc = NULL,
  maintitle = "", showlines = TRUE, showpoints = TRUE, ylim = c(0, 1),
  angle = -45, density = 20, col = "black", jitter = NULL,
  divisions = 25, pages = 0, xlab = "Distance",
  ylab = "Detection probability", subtitle = TRUE, ...)

Arguments

x

fitted model from ddf

which

index to specify which plots should be produced.

1 Unconditional detection function for observer 1
2 Conditional detection function plot (1|2)
breaks

user define breakpoints

nc

number of equal-width bins for histogram

maintitle

main title line for each plot

showlines

logical variable; if TRUE a line representing the average detection probability is plotted

showpoints

logical variable; if TRUE plots predicted value for each observation

ylim

range of y axis; defaults to (0,1)

angle

shading angle for hatching

density

shading density for hatching

col

plotting colour

jitter

scaling option for plotting points. Jitter is applied to points by multiplying the fitted value by a random draw from a normal distribution with mean 1 and sd jitter.

divisions

number of divisions for averaging line values; default = 25

pages

the number of pages over which to spread the plots. For example, if pages=1 then all plots will be displayed on one page. Default is 0, which prompts the user for the next plot to be displayed.

xlab

label for x-axis

ylab

label for y-axis

subtitle

if TRUE, shows plot type as sub-title

...

other graphical parameters, passed to the plotting functions (plot, hist, lines, points, etc)

Details

The structure of the histogram can be controlled by the user-defined arguments nc or breaks. The observation specific detection probabilities along with the line representing the fitted average detection probability.

It is not intended for the user to call plot.io.fi but its arguments are documented here. Instead the generic plot command should be used and it will call the appropriate function based on the class of the ddf object.

Author(s)

Jeff Laake, Jon Bishop, David Borchers

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.