mdsunique {asymmetry} | R Documentation |

## MDS Model with Unique Dimensions

### Description

This asymmetric MDS model proposed by Holman (1979) and further analyzed by Bentler & Weeks (1982) has both common and unique dimensions. The common dimensions are shared by all other objects, whereas unique dimension apply to one object. A unique dimension has a non zero value for only one object, the coordinates for the other objects are zero. There are as many unique dimensions as there are objects. An asymmetric version of this model has two sets of unique dimensions: one for the rows and one for the columns. The distance in this model is defined as:

`d_{ij}(X)=\sqrt{\sum_{s=1}^p (x_{is}-x_{js})^2 + r_{i}^{2}+c_{j}^{2}}.`

### Usage

```
mdsunique(data, weight = NULL, ndim = 2, verbose = FALSE, itmax = 125, eps = 1e-12)
```

### Arguments

`data` |
Asymmetric dissimilarity matrix |

`weight` |
Optional non-negative matrix with weights, if no weights are given all weights are set equal to one |

`ndim` |
Number of dimensions |

`verbose` |
If true, prints the iteration history to screen |

`itmax` |
Maximum number of iterations |

`eps` |
Convergence criterion for Stress |

### Value

`ndim` |
Number of dimensions of the configuration |

`fulldim` |
Number of dimensions of the full model, this equals |

`stress` |
The raw stress for this model |

`confi` |
Returns the configuration matrix of shared dimensions of this multidimensional scaling model |

`X` |
Returns the configuration matrix of the full model consisting of shared and unique dimensions |

`niter` |
The number of iterations for the algorithm to converge |

`nobj` |
The number of objects in this model |

`resid` |
A matrix with raw residuals |

`model` |
Name of this asymmetric multidimensional scaling model |

`row` |
The unique dimensions for the rows |

`col` |
The unique dimensions for the columns |

`unique` |
The unique dimensions |

### Examples

```
## Not run:
data("studentmigration")
mm<-studentmigration
mm[mm==0]<-.5 # replace zeroes by a small number
mm <- -log(mm/sum(mm)) # convert similarities to dissimilarities
v<-mdsunique(mm, ndim = 2, itmax = 2100, verbose=FALSE, eps = .0000000001)
plot(v, yplus = .3)
## End(Not run)
```

*asymmetry*version 2.0.4 Index]