Knet | R Documentation |
Compute the geometrically-corrected K
function
for a point pattern on a linear network.
Knet(X, r = NULL, freq, ..., verbose=FALSE)
X |
Point pattern on a linear network (object of class |
r |
Optional. Numeric vector of values of the function argument |
freq |
Vector of frequencies corresponding to the point events on the network. The length of this vector should be equal to the number of points on the network. The default frequency is one for every point on the network. |
... |
Ignored. |
verbose |
A logical for printing iteration number corresponding to each point event on the network. |
This command computes the geometrically-corrected K
function,
proposed by Ang et al (2012), from point pattern data on a linear
network.
The algorithm used in this computation is discussed in Rakshit et al (2019).
The spatstat function linearK
is usable (and slightly faster) for the same purpose
for small datasets, but requires substantial amounts of memory.
For larger datasets, the function Knet
is much more efficient.
Function value table (object of class "fv"
).
Suman Rakshit (modified by Adrian Baddeley)
Ang, Q.W., Baddeley, A. and Nair, G. (2012) Geometrically corrected second-order analysis of events on a linear network, with applications to ecology and criminology. Scandinavian Journal of Statistics 39, 591–617.
Rakshit, S., Baddeley, A. and Nair, G. (2019)
Efficient code for second order analysis of events on a linear network.
Journal of Statistical Software 90 (1) 1–37.
DOI: 10.18637/jss.v090.i01
UC <- unmark(chicago)
r <- seq(0, 1000, length = 41)
K <- Knet(UC, r = r)
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