R: Simplified Analysis in Principal Coordinates

pcoscaled {ade4} | R Documentation

## Simplified Analysis in Principal Coordinates

### Description

performs a simplified analysis in principal coordinates, using an object of class `dist`.

### Usage

    pcoscaled(distmat, tol = 1e-07)

### Arguments

`distmat` | an object of class `dist`
`tol` | a tolerance threshold, an eigenvalue is considered as positive if it is larger than `-tol*lambda1` where `lambda1` is the largest eigenvalue

### Value

returns a data frame containing the Euclidean representation of the distance matrix with a total inertia equal to 1

### Author(s)

Daniel Chessel

### References

Gower, J. C. (1966) Some distance properties of latent root and vector methods used in multivariate analysis. Biometrika, 53, 325–338.

### Examples

        a <- 1 / sqrt(3) - 0.2
        w <- matrix(c(0,0.8,0.8,a,0.8,0,0.8,a,
            0.8,0.8,0,a,a,a,a,0),4,4)
        w <- as.dist(w)
        w <- cailliez(w)
        w
        pcoscaled(w)
        dist(pcoscaled(w)) # w
        dist(pcoscaled(2 * w)) # the same
        sum(pcoscaled(w)^2) # unity

[Package ade4 version 1.7-18 Index]