Description Usage Arguments Details Value See Also Examples

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

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
## S3 method for class 'secr'
plot(x, newdata = NULL, add = FALSE,
sigmatick = FALSE, rgr = FALSE, limits = FALSE, alpha = 0.05,
xval = 0:200, ylim = NULL, xlab = NULL, ylab = NULL, ...)
## S3 method for class 'secrlist'
plot(x, newdata = NULL, add = FALSE,
sigmatick = FALSE, rgr = FALSE, limits = FALSE, alpha = 0.05,
xval = 0:200, ylim = NULL, xlab = NULL, ylab = NULL, ...,
overlay = TRUE)
detectfnplot (detectfn, pars, details = NULL, add = FALSE,
sigmatick = FALSE, rgr = FALSE, xval = 0:200, ylim = NULL,
xlab = NULL, ylab = NULL, ...)
attenuationplot (pars, add = FALSE, spherical = TRUE,
xval = 0:200, ylim = NULL, xlab = NULL, ylab = NULL, ...)
``` |

`x` |
an |

`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 |

`overlay` |
logical; if TRUE then automatically |

`detectfn` |
integer code or character string for shape of detection function 0 = halfnormal etc. – see detectfn |

`pars` |
list, vector or matrix of parameter values |

`details` |
list of ancillary parameters |

`spherical` |
logical for whether to include spherical spreading term |

`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. `pars`

maybe a list
as from `detectpar`

; it is first coerced to a numeric vector
with `unlist`

. Parameter values must be in the expected order
(e.g. g0, sigma, z). 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.

`attenuationplot`

plots the expected decline in signal strength
with distance, given parameters *beta0* and
*beta1* for a log-linear model of sound attenuation.

`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).

`Detection functions`

, `plot`

, `secr`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ```
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))
## add a function with louder source and spherical spreading...
detectfnplot (detectfn = 11, c(110, -0.3, 5), details =
list(cutval = 40), add = TRUE, col = "red")
## matching sound attenuation curves; `spherical-only' dashed line
attenuationplot (c(70, -0.3), spherical = FALSE, ylim=c(-10,110))
attenuationplot (c(110, 0), spherical = TRUE, add=TRUE, lty=2)
attenuationplot (c(110, -0.3), spherical = TRUE, add = TRUE,
col = "red")
``` |

secr documentation built on May 30, 2017, 12:15 a.m.

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