sliwinltr {adehabitat} | R Documentation |
This function applies a function on an object of class "ltraj", using a sliding window.
sliwinltr(ltraj, fun, step, type = c("locs", "time"), units = c("sec", "min", "hour", "day"), plotit = TRUE, ...)
ltraj |
an object of class ltraj |
fun |
the function to be applied, implying at least one of the
descriptive parameters in the object of class ltraj (see
below) |
step |
the half-width of the sliding window. If
type=="locs" , it is a number of relocations. If
type=="time" it is a number described by units |
type |
character string. If type == "locs" , step
describes a number of relocations: if type == "time" ,
step describes a time lag. |
units |
if type == "time" , the time units described by
step . Ignored otherwise |
plotit |
logical. Whether the result should be plotted |
... |
additional arguments to be passed to the function
rec |
An object of class ltraj is a list with one component per burst of
relocations. The function fun
is applied to each burst of
relocations. This burst of relocations should be refered as x
in fun
. For example, to compute the mean of the distance
between successive relocations, the function fun
is equal to
function(x) mean(x$dist)
.
Do not forget that some of the descriptive parameters in the object
ltraj
may contain missing values (see
help(ltraj)
). The function should therefore specify how to
manage these missing values.
If type=="locs"
, a list with one component per burst of
relocation containing the smoothed values for each relocation.
If type=="locs"
, a list with one component per burst of
relocation. Each component is a data frame containing the time and
the corresponding smoothed values for each date.
Clement Calenge clement.calenge@oncfs.gouv.fr
ltraj
for additional information about objects
of class ltraj
data(capreotf) ## computes the average speed of the roe deer in a moving window of width ## equal to 60 minutes toto <- sliwinltr(capreotf, function(x) mean(x$dist/x$dt, na.rm = TRUE), step = 30, type = "time", units = "min") ## zoom before the peak head(toto[[1]]) plot(toto[[1]][1:538,], ty="l")