R: Soft Ordinal Embedding (SOE)

SOE {loe} | R Documentation

## Soft Ordinal Embedding (SOE)

### Description

Performs SOE for a given part of ordinal informaiton.

### Usage

    SOE(CM, N, p = 2, c = 0.1, maxit = 1000, report = 100, iniX = "rand",rnd=10000)

### Arguments

`CM` | A matrix whose rows represent ordinal information: A row vector (i,j,k,l) means xi_{ij} < xi_{kl}, where xi_{ij} is a dissimilarity between object i and object j. If the number of given ordinal comparisons is more than 100000, then SOE randomly chooses `rnd` ordinal comarisons from given comparisons.
`N` | The number of objects.
`p` | The number of dimensions.
`c` | Scale parameter which only takes strictly positive value.
`maxit` | Maximum number of iteretions.
`report` | The frequency of reports. Defaults to every 100 iterations.
`iniX` | Matrix with starting values for embedding (optional).
`rnd` | The number of ordinal comarisons which are randomly chosen from given ordinal comparisons `CM`. `rnd` is used only if the number of given ordinal comparisons is more than 100000.

### Value

`SOE` returns a list with components:

`X` | The best corrdinate matrix with p columns whose rows give the coordinates of objects.
`str` | The value of the stress function of SOE corresponding to `X`.

### Author(s)

Yoshikazu Terada

### Examples

    library(MASS)
    data(eurodist)
    OIF <- get.order(as.matrix(eurodist))
    sid <- sample(1:nrow(OIF))
    POI <- OIF[sid[1:1000],]
    result <- SOE(CM=POI, N=nrow(as.matrix(eurodist)),p=2, c=0.1,maxit =1000,report=100)
    plot(result$X,type="n",xlab="Dim. 1", ylab="Dim. 2")
    text(result$X,rownames(as.matrix(eurodist)),cex=1)

[Package loe version 1.1 Index]