Compute cost of edges
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)
nb |
An object of |
data |
A matrix with observations in the nodes. |
id |
Node index to compute the cost |
id.neigh |
Idex of neighbours nodes of node |
method |
Character or function to declare distance method.
If |
p |
The power of the Minkowski distance. |
cov |
The covariance matrix used to compute the mahalanobis distance. |
inverted |
logical. If 'TRUE', 'cov' is supposed to contain the inverse of the covariance matrix. |
A object of nbdist
class. See nbdists
for
details.
The neighbours must be a connected graph.
Elias T. Krainski and Renato M. Assuncao
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