mds {chroGPS} | R Documentation

## Metric and non-metric Multidimensional Scaling for a distGPS object.

### Description

Generation of Multidimensional Scaling objects for the dissimilarities between elements given as an input in a `distGPS` object. Metric and non-metric algorithms are available, as well as an optimization algorithm for improving r-square correlation between observed and approximated distances. The MDS calculation for a given distance matrix can be splitted into smaller individual tasks and run in parallel, greatly improving CPU time and system memory usage. The S4 accessor functions `getR2, getStress, getPoints` retrieve R-square correlation, stress and points stored within a `mds` object respectively. The function `is.adj` is useful to know if a certain chroGPS MDS map has been adjusted by Procrustes or not (see help for `procrustesAdj` for details.)

### Usage

    mds(d, m = NULL, k = 2, type = "classic", add = FALSE, cor.method = "pearson", splitMDS = FALSE, split = 0.26, overlap = 0.025, stepSize=0.01, reshuffle = TRUE, set.seed = 149, mc.cores = 1, ...)
    getR2(m)
    getStress(m)
    getPoints(m)

### Arguments

`d` | Object of class `distGPS` with the pairwise observed dissimilarities between elements, a distance matrix.
`m` | (Optional). Object of class `mds` with a MDS object generated from the distances in `d`. Only MDS type "boostMDS" is available. The mds function performs an optimization of the approximated distances in `m` in order to improve r-square correlation between them and the observed dissimilarities en `d`, maximizing goodness of fit.
`k` | Dimensionality of the reconstructed space, typically set to 2 or 3.
`type` | Set to `"classic"` to perform classical MDS (uses function `cmdscale` from package `stats`). Set to `"isoMDS"` to use Kruskal's non-metric MDS (uses function `isoMDS` from package `MASS`) Set to "boostMDS" to perform r-square optimization of a pre-computed input MDS for that distance matrix.
`add` | Logical indicating if an additive constant c* should be computed, and added to the non-diagonal dissimilarities such that all n-1 eigenvalues are non-negative in `cmdscale`.
`cor.method` | A character string indicating which correlation coefficient (or covariance) is to be computed. One of "pearson" (default), "kendall", or "spearman", can be abbreviated.
`splitMDS` | Set to `TRUE` to perform computation of the MDS in parallel (see parameters below).
`split` | Proportion of elements to include in each (but last) distance submatrix.
`overlap` | Proportion of elements to be used as common anchor points between two adjacent distance submatrixes. These points will be used as spatial references to stitch each two adjacent MDS objects by Procrustes.
`stepSize` | Size for the quadratic search step to be used for R-square optimization if `boostMDS` is called, see specific help function for details.
`reshuffle` | Set to TRUE to perform random resampling of the input distance matrix before splitting it for parallel computation. This is often necessary to sufficiently capture the inherent variability of the data in each distance submatrix so that the stitching process can work properly, as the original data may present an arbitrary sorting of some kind. If a previous resampling of the data has been performed, this is not necessary.
`set.seed` | Random seed to perform the resampling.
`mc.cores` | Number of cores to be passed to the `mclapply` function from the `parallel` package, used to perform the parallel MDS computations.
`...` | Additional parameters passed to `cmdscale`, `isoMDS` or `boostMDS`, see each individual help file for details.

### Value

The function returns a `mds` object. See help ("mds-Class") for details.

### Methods

mds

  `signature(d = "distGPS", m = "missing")`: Creates a `mds` object with points in a k-dimensional space approximating the pairwise distances in `d`.

mds

  `signature(d = "distGPS", m = "mds")`: For the observed dissimilarities in `d` and a valid spatial representation of them in `m`, the function returns a `mds` object with an optimized representation of `d` in terms of R-square. The MDS stress measure is also returned. See help for `boostMDS` for details.

plot

  `signature(m = "mds")`: S4 plot method for `mds` objects.

### Author(s)

Oscar Reina

### See Also

See functions cmdscale, isoMDS from package `MASS`.

### Examples

    x <- rbind(c(rep(0,15),rep(1,5)),c(rep(0,15),rep(1,5)),c(rep(0,19),1),c(rep(1,5),rep(0,15)))
    rownames(x) <- letters[1:4]
    d <- distGPS(x,metric='tanimoto',uniqueRows=TRUE)
    mds1 <- mds(d)
    mds1
    plot(mds1)
    #gps2xgmml(mds1, fname='chroGPS_factors.xgmml', fontSize=4,col=col2hex('red'), cex=8)

[Package chroGPS version 2.2.0 Index]