Plot unconditional detection function from distance sampling model
Plots unconditional detection function for observer=obs observations
overlays histogram, average detection function and values for individual
observations data. Internal function called by plot
methods.
plot_uncond( model, obs, xmat, gxvalues, nc, finebr, breaks, showpoints, showlines, maintitle, ylim, return.lines = FALSE, angle = -45, density = 20, col = "black", jitter = NULL, xlab = "Distance", ylab = "Detection probability", subtitle = TRUE, ... )
model |
fitted model from |
obs |
value of observer for plot |
xmat |
processed data |
gxvalues |
detection function values for each observation |
nc |
number of equal-width bins for histogram |
finebr |
fine break values over which line is averaged |
breaks |
user define breakpoints |
showpoints |
logical variable; if TRUE plots predicted value for each observation |
showlines |
logical variable; if TRUE plots average predicted value line |
maintitle |
main title line for each plot |
ylim |
range of y axis; defaults to (0,1) |
return.lines |
if TRUE, returns values for line |
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. |
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
( |
if return.lines==TRUE
returns dataframe average.line
otherwise just plots
Jeff Laake, Jon Bishop, David Borchers
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