plot.secr {secr} | R Documentation

## Plot Detection Functions

### Description

Plot detection functions using estimates of parameters in an secr object, or as provided by the user.

### Usage

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

    detectfnplot(detectfn, pars, details = NULL, add = FALSE,
        sigmatick = FALSE, rgr = FALSE, xval = 0:200, ylim = NULL,
        xlab = NULL, ylab = NULL, ...)

### Arguments

`x` | an `secr` 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`
`detectfn` | integer code for detection function 0 halfnormal, 1 hazard-rate etc.
`pars` | vector or matrix of parameter values
`details` | list of ancillary parameters

### Details

`newdata` is usually NULL, in which case one curve is plotted for each session and group. Otherwise, `predict.secr` 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'.

`detectfnplot` is an alternative in which the user nominates the type of function and provides parameter values. If pars is a matrix then a separate curve is plotted with the parameter values in each row.

For `detectfnplot` the signal threshold parameters 'cutval' and 'spherical' should be provided in `details` (see examples).

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 is assumed to be normal on the logit scale; limits are back-transformed from that scale.

### Value

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

### Author(s)

Murray Efford murray.efford@otago.ac.nz

### See Also

`detection functions`, `plot`, `secr`

### Examples

    data(secrdemo)
    plot (secrdemo.b, xval = 0:100, ylim = c(0, 0.4))
    ## Add recapture probability
    plot (secrdemo.b, newdata = data.frame(b = 1), add = TRUE,
        col='red')

    ## signal strength detection: 70dB at source, attenuation
    ## 0.3dB/m, sdS 5dB; detection threshold 40 dB.
    detectfnplot (detectfn = 10, c(70, -0.3, 5), details =
        list(cutval = 40, spherical = FALSE))

    ## add a function with louder source and spherical spreading...
    detectfnplot (detectfn = 10, c(110, -0.3, 5), details =
        list(cutval = 40, spherical = TRUE), add = TRUE, col='red')

[Package secr version 1.3.0 Index]