plot.ipsecr: Plot Detection Functions

Description

Plot detection functions using estimates of parameters in an ipsecr object.

Usage

# S3 method for ipsecr
plot(x, newdata = NULL, add = FALSE,
    sigmatick = FALSE, rgr = FALSE, limits = FALSE, alpha = 0.05,
    xval = 0:200, ylim = NULL, xlab = NULL, ylab = NULL, ...)

Value

plot.ipsecr invisibly returns a dataframe of the plotted values (or a list of dataframes in the case that newdata has more than one row).

Arguments

x: an ipsecr object
newdata: dataframe of data to form estimates
add: logical to add curve(s) to an existing plot
sigmatick: logical; if TRUE the scale parameter sigma is shown by a vertical line
rgr: logical; if TRUE a scaled curve r.g(r) is plotted instead of g(r)
limits: logical; if TRUE pointwise confidence limits are drawn
alpha: alpha level for confidence intervals
xval: vector of distances at for which detection to be plotted
ylim: vector length 2 giving limits of y axis
xlab: label for x axis
ylab: label for y axis
...: arguments to pass to lines

Details

newdata is usually NULL, in which case one curve is plotted for each session and group. Otherwise, predict.ipsecr is used to form estimates and plot a curve for each row in newdata.

If axis labels are not provided they default to `Distance (m)' and `Detection probability' or `Detection lambda'.

Approximate confidence limits for g(r) are calculated using a numerical first-order delta-method approximation to the standard error at each xval. The distribution of g(r) is assumed to be normal on the logit scale for non-hazard functions (detectfn 0:13). For hazard detection functions (detectfn 14:18) the hazard is assumed (from version 3.1.1) to be distributed normally on the log scale. Limits are back-transformed to the probability scale g(r).

Examples

Run this code


plot (ipsecrdemo, xval = 0:100, ylim = c(0, 0.4))