getMeanSD(xy)
maskarea(mask, sessnum = 1)
masklength(mask, sessnum = 1)
edist(xy1, xy2)
nedist(xy1, xy2, mask, inf = Inf, ...)transitiongetMeanSD, a dataframe with columns `x' and `y' and two
rows, mean and SD.
For maskarea, the summed area of mask cells in hectares (ha).
For masklength, the summed length of mask cells in kilometers (km).
For edist and nedist, a matrix with dim = c(nrow(xy1), nrow(xy2)).getmeanSD is used by make.mask to standardize
mask coordinates.
For masklength the input should be a linear mask from edist computes the Euclidean distance between each point in xy1
and each point in xy2. (This duplicates the functionality of `rdist'
in package nedist computes the non-Euclidean distance between each point
in xy1 and each point in xy2, in two dimensions. The calculation uses
mask. By default, points within a 16-point
neighbourhood are considered `adjacent'. Distances are obtained by
Dijkstra's (1959) algorithm as least cost paths through the graph of
all points in the mask.
nedist has some subtle options. If `mask' is missing then the
transition layer will be formed from `xy2'. If `mask' has a covariate
named `noneuc' then this will be used to weight distances. The ...argument of nedist allows the user to vary arguments of
transition (defaults transitionFunction =
mean and directions = 16). Be warned this can lead to unexpected
results! Point pairs that are completely separated receive the
distance +Inf unless a finite value is provided for the argument
`inf'. See
nedist.