spdep (version 0.5-3)

ssw: Compute the sum of dissimilarity

Description

This function computes the sum of dissimilarity between each observation and the mean (scalar of vector) of the observations.

Usage

ssw(data, id, method = c("euclidean", "maximum", 
    "manhattan", "canberra", "binary", "minkowski", "mahalanobis", 
    "other"), p = 2, cov, inverted = FALSE, otherfun)

Arguments

data

A matrix with observations in the nodes.

id

Node index to compute the cost

method

Character for declare the distance method. For "euclidean", "maximum", "manhattan", "canberra", "binary" and "minkowski", see dist for details, because this function as used to compute the di

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.

otherfun

A user defined function to compute the distance

Value

• A numeric, the sum of dissimilarity between the observations id of data and the mean (scalar of vector) of this observations.

See Also

See Also as nbcost

Examples

data(USArrests)
n <- nrow(USArrests)
ssw(USArrests, 1:n)
ssw(USArrests, 1:(n/2))
ssw(USArrests, (n/2+1):n)
ssw(USArrests, 1:(n/2)) + ssw(USArrests, (n/2+1):n)