Add covariate levels detection function plots
Add a line or lines to a plot of the detection function which correspond to a a given covariate combination. These can be particularly useful when there is a small number of factor levels or if quantiles of a continuous covariate are specified.
add_df_covar_line(ddf, data, ndist = 250, pdf = FALSE, breaks = "Sturges", ...)
ddf |
a fitted detection function object. |
data |
a |
ndist |
number of distances at which to evaluate the detection function. |
pdf |
should the line be drawn on the probability density scale; ignored for line transects. |
breaks |
required to ensure that PDF lines are the right size, should match what is supplied to original |
... |
extra arguments to give to |
All covariates must be specified in data
. Plots can become quite busy when this approach is used. It may be useful to fix some covariates at their median level and plot set values of a covariate of interest. For example setting weather (e.g., Beaufort) to its median and plotting levels of observer, then creating a second plot for a fixed observer with levels of weather.
invisibly, the values of detectability over the truncation range.
David L Miller
## Not run: # fit an example model data(book.tee.data) egdata <- book.tee.data$book.tee.dataframe result <- ddf(dsmodel = ~mcds(key = "hn", formula = ~sex), data = egdata[egdata$observer==1, ], method = "ds", meta.data = list(width = 4)) # make a base plot, showpoints=FALSE makes the plot less busy plot(result, showpoints=FALSE) # add lines for sex one at a time add_df_covar_line(result, data.frame(sex=0), lty=2) add_df_covar_line(result, data.frame(sex=1), lty=3) # add a legend legend(3, 1, c("Average", "sex==0", "sex==1"), lty=1:3) # alternatively we can add both at once # fixing line type and varying colour plot(result, showpoints=FALSE) add_df_covar_line(result, data.frame(sex=c(0,1)), lty=1, col=c("red", "green")) # add a legend legend(3, 1, c("Average", "sex==0", "sex==1"), lty=1, col=c("black", "red", "green")) ## End(Not run)
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