plot.ds | R Documentation |
Plots the fitted detection function(s) with a histogram of the observed distances to compare visually the fitted model and data.
## S3 method for class 'ds'
plot(
x,
which = 2,
breaks = NULL,
nc = NULL,
jitter.v = rep(0, 3),
showpoints = TRUE,
subset = NULL,
pl.col = "lightgrey",
pl.den = NULL,
pl.ang = NULL,
main = NULL,
pages = 0,
pdf = FALSE,
ylim = NULL,
xlab = "Distance",
ylab = NULL,
...
)
x |
fitted model from | ||||
which |
index to specify which plots should be produced:
| ||||
breaks |
user defined breakpoints | ||||
nc |
number of equal width bins for histogram | ||||
jitter.v |
apply jitter to points by multiplying the fitted value by a
random draw from a normal distribution with mean 1 and sd | ||||
showpoints |
logical variable; if | ||||
subset |
subset of data to plot. | ||||
pl.col |
colour for histogram bars. | ||||
pl.den |
shading density for histogram bars. | ||||
pl.ang |
shading angle for histogram bars. | ||||
main |
plot title. | ||||
pages |
the number of pages over which to spread the plots. For
example, if | ||||
pdf |
plot the histogram of distances with the PDF of the probability of detection overlaid. Ignored (with warning) for line transect models. | ||||
ylim |
vertical axis limits. | ||||
xlab |
horizontal axis label (defaults to "Distance"). | ||||
ylab |
vertical axis label (default automatically set depending on plot type). | ||||
... |
other graphical parameters, passed to the plotting functions
( |
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.ds
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.
Just plots.
Jeff Laake, Jon Bishop, David Borchers, David L Miller
add_df_covar_line
# fit a model to the tee data
data(book.tee.data)
egdata <- book.tee.data$book.tee.dataframe
xx <- ddf(dsmodel=~mcds(key="hn", formula=~sex),
data=egdata[egdata$observer==1, ],
method="ds", meta.data=list(width=4))
# not showing predicted probabilities
plot(xx, breaks=c(0, 0.5, 1, 2, 3, 4), showpoints=FALSE)
# two subsets
plot(xx, breaks=c(0, 0.5, 1, 2, 3, 4), subset=sex==0)
plot(xx, breaks=c(0, 0.5, 1, 2, 3, 4), subset=sex==1)
# put both plots on one page
plot(xx, breaks=c(0, 0.5, 1, 2, 3, 4), pages=1, which=1:2)
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