dbar is the mean distance between consecutive capture locations,
pooled over individuals (e.g. Efford 2004). moves returns the
raw distances.
MMDM (for `Mean Maximum Distance Moved') is the average maximum
distance between detections of each individual i.e. the observed range
length averaged over individuals (Otis et al. 1978).
ARL or `Asymptotic Range Length') is obtained by fitting an
exponential curve to the scatter of observed individual range length vs
the number of detections of each individual (Jett and Nichols 1987: 889).
RPSV (for `Root Pooled Spatial Variance') is a measure of the 2-D
dispersion of the locations at which individual animals are detected,
pooled over individuals (cf Calhoun and Casby 1958, Slade and Swihart 1983).dbar(capthist, userdist = NULL, mask = NULL)
MMDM(capthist, min.recapt = 1, full = FALSE, userdist = NULL, mask = NULL)
ARL(capthist, min.recapt = 1, plt = FALSE, full = FALSE, userdist = NULL, mask = NULL)
moves(capthist, userdist = NULL, mask = NULL)
RPSV(capthist, CC = FALSE)capthistcapthist
is a multi-session list.
The full argument may be used with MMDM and ARL to
return more extensive output, particularly the observed range length for
each detection history.dbar is defined as --
$$\overline{d}=\frac{\sum\limits _{i=1}^{n}
\sum\limits _{j=1}^{n_i - 1}
\sqrt{(x_{i,j}-x_{i,j+1})^2 + (y_{i,j}-y_{i,j+1})^2}}
{\sum\limits _{i=1}^{n} (n_i-1)}$$
When CC = FALSE, RPSV is defined as --
$$RPSV = \sqrt{
\frac {\sum\limits _{i=1}^{n} \sum\limits _{j=1}^{n_i} [
(x_{i,j} - \overline x_i)^2 + (y_{i,j} - \overline y_i)^2
]}{\sum\limits _{i=1}^{n} (n_i-1) - 1}}$$.
Otherwise (CC = TRUE), RPSV uses the formula of Calhoun
and Casby (1958) with a different denominator --
$$s = \sqrt{
\frac {\sum\limits _{i=1}^{n} \sum\limits _{j=1}^{n_i} [
(x_{i,j} - \overline x_i)^2 + (y_{i,j} - \overline y_i)^2
]}{2\sum\limits _{i=1}^{n} (n_i-1)}}$$.
The Calhoun and Casby formula (offered from 2.9.1) correctly estimates $\sigma$
when trapping is on an infinite, fine grid, and is preferred
for this reason. The original RPSV
(CC = FALSE) is retained as the default for compatibility with
previous versions of dbar and RPSV have a specific role as proxies for
detection scale in inverse-prediction estimation of density (Efford
2004; see ip.secr).
RPSV is used in autoini to obtain plausible starting
values for maximum likelihood estimation.
MMDM and ARL discard data from detection histories
containing fewer than min.recapt+1 detections.
The userdist option is included for exotic non-Euclidean cases
(see e.g. secr.fit details). RPSV is not defined for
non-Euclidean distances.autoinidbar(captdata)
RPSV(captdata)
RPSV(captdata, CC = TRUE)Run the code above in your browser using DataLab