R: Conciseness of Presentation Measures

stress {cba} | R Documentation

## Conciseness of Presentation Measures

### Description

Compute different types of conciseness of presentation measures.

### Usage

    stress(x, rows = NULL, cols = NULL, type = "moore")

    stress.dist(x, rows = NULL, cols = NULL, bycol = FALSE,
                type = "moore")

### Arguments

`x` | a matrix object.
`rows` | a subscript vector indexing the rows.
`cols` | a subscript vector indexing the columns.
`bycol` | logical for computation over the columns.
`type` | the type of neighborhood to use.

### Details

Function `stress` computes the sum of squared distances of each matrix entry from its adjacent entries. The following types of neighborhoods are available:

`moore`:

  comprises the eight adjacent entries (five at the margins and three at the corners).

`neumann`:

  comprises the four adjacent entries (three at the margins and two at the corners).

Function `stress.dist` computes the auto-distance matrix for each pair of rows (or columns) given one of the above stress measures. Note that the result depends on the ordering of the unused dimension.

As the computation can be reduced to summing the edge distances between any two neighboring points, only half of the value of the proposed measures is reported.

Row and/or column indexes (or labels) can be supplied to test specific orderings, as well as subsets of indexes (labels).

Note that the matrix should be normalized so that the distance computation is meaningful.

### Value

`stress` returns a scalar real, i.e. half of the global stress measure.

`stress.dist` returns an object of class `dist`, i.e. a lower triangular matrix in column format.

### Author(s)

Christian Buchta

### See Also

`dist` for general distance computation.

### Examples

    ##
    x1 <- matrix(sample(c(FALSE,TRUE),25,rep=TRUE),ncol=5)
    stress(x1)
    stress(x1, type="neumann")
    ##
    x2 <- cbind(rbind(matrix(1,4,4),matrix(0,4,4)),
    	    rbind(matrix(0,4,4),matrix(1,4,4)))
    stress.dist(x2)
    stress.dist(x2, bycol=TRUE)
    stress.dist(x2, type="neumann")

[Package cba version 0.2-21 Index]