The cost of each edge is the distance between it nodes. This function compute this distance using a data.frame with observations vector in each node.
nbcost(data, id, id.neigh, method = c("euclidean", "maximum",
"manhattan", "canberra", "binary", "minkowski", "mahalanobis"),
p = 2, cov, inverted = FALSE)
nbcosts(nb, data, method = c("euclidean", "maximum",
"manhattan", "canberra", "binary", "minkowski", "mahalanobis"),
p = 2, cov, inverted = FALSE)
A object of nbdist
class. See nbdists
for
details.
An object of nb
class. See poly2nb
for
details.
A matrix with observations in the nodes.
Node index to compute the cost
Idex of neighbours nodes of node id
Character or function to declare distance method.
If method
is character, method must be "mahalanobis" or
"euclidean", "maximum", "manhattan", "canberra", "binary"
or "minkowisk".
If method
is one of "euclidean", "maximum",
"manhattan", "canberra", "binary" or "minkowisk", see
dist
for details,
because this function as used to compute the distance.
If method="mahalanobis"
, the mahalanobis distance
is computed between neighbour areas.
If method
is a function
, this function is
used to compute the distance.
The power of the Minkowski distance.
The covariance matrix used to compute the mahalanobis distance.
logical. If 'TRUE', 'cov' is supposed to contain the inverse of the covariance matrix.
Elias T. Krainski and Renato M. Assuncao
See Also as nbdists
, nb2listw