R: Summary Statistics for Spectral Map Analysis...

summary.mpm {mpm} | R Documentation

## Summary Statistics for Spectral Map Analysis...

### Description

Summary Statistics for Spectral Map Analysis Summary method for object of class `mpm`.

### Usage

    ## S3 method for class 'mpm'
    summary(object, maxdim=4, ...)

### Arguments

`object` | an object of class `mpm` resulting from a call to `mpm`
`maxdim` | maximum number of principal factors to be reported. Defaults to `4`
`...` | further arguments; currently none are used

### Details

The function `summary.mpm` computes and returns a list of summary statistics of the spectral map analysis given in `x`.

### Value

An object of class `summary.mpm` with the following components:

`call` | the call to `mpm`
`Vxy` | sum of eigenvalues
`VPF` | a matrix with on the first line the eigenvalues and on the second line the cumulative eigenvalues of each of the principal factors (`PRF1` to `PRFmaxdim`) followed by the residual eigenvalues and the total eigenvalue.
`Rows` | a data frame with summary statistics for the row-items, as described below.
`Columns` | a data frame with with summary statistics for the column-items, as described below. The `Rows` and `Columns` data frames contain the following columns:
`Posit` | binary indication of whether the row or column was positioned (`1`) or not (`0`).
`Weight` | weight applied to the row or column in the function `mpm`.
`PRF1-PRFmaxdim` | factor scores or loadings for the first `maxdim` factors using eigenvalue scaling.
`Resid` | residual score or loading not accounted for by the first `maxdim` factors.
`Norm` | length of the vector representing the row or column in factor space.
`Contrib` | contribution of row or column to the sum of eigenvalues.
`Accuracy` | accuracy of the representation of the row or column by means of the first `maxdim` principal factors.

### Author(s)

Luc Wouters

### References

Wouters, L., Goehlmann, H., Bijnens, L., Kass, S.U., Molenberghs, G., Lewi, P.J. (2003). Graphical exploration of gene expression data: a comparative study of three multivariate methods. Biometrics 59, 1131-1140.

### See Also

`mpm`, `plot.mpm`

### Examples

    # Example 1 weighted spectral map analysis Golub data
    data(Golub)
    r.sma <- mpm(Golub[,1:39], row.weight = "mean", col.weight = "mean")
    # summary report
    summary(r.sma)
    # Example 2 using print function
    data(Famin81A)
    r.fam <- mpm(Famin81A, row.weight = "mean", col.weight = "mean")
    r.sum <- summary(r.fam)
    print(r.sum, what = "all")

[Package mpm version 1.0-22 Index]