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