# ssw: Compute the sum of dissimilarity In spdep: Spatial Dependence: Weighting Schemes, Statistics

## Description

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

## Usage

 ```1 2 3``` ```ssw(data, id, method = c("euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski", "mahalanobis"), p = 2, cov, inverted = FALSE) ```

## Arguments

 `data` A matrix with observations in the nodes. `id` Node index to compute the cost `method` 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. `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.

## Value

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

## Author(s)

Elias T. Krainski and Renato M. Assuncao

## See Also

See Also as `nbcost`

## Examples

 ```1 2 3 4 5 6``` ```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) ```

spdep documentation built on May 23, 2021, 5:06 p.m.