Description Usage Arguments Details Value Author(s) References Examples
Compute score and orthogonal distances for an object (derived from)Pcaclass
.
1  pca.distances(obj, data, r, crit=0.975)

obj 
an object of class (derived from) 
data 
The data matrix for which the 
r 
rank of data 
crit 
Criterion to use for computing the cutoff values. 
This function calculates the score and orthogonal distances and the appropriate cutoff values for identifying outlying observations. The computed values are used to create a vector a of flags, one for each observation, identifying the outliers.
An S4 object of class derived from the virtual class Pcaclass

the same object passed to the function, but with the score and orthogonal
distances as well as their cutoff values and the corresponding flags appended to it.
Valentin Todorov valentin.todorov@chello.at
M. Hubert, P. J. Rousseeuw, K. Vanden Branden (2005), ROBPCA: a new approach to robust principal components analysis, Technometrics, 47, 64–79.
Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. Journal of Statistical Software, 32(3), 1–47. URL http://www.jstatsoft.org/v32/i03/.
1 2 3 4 5  ## PCA of the Hawkins Bradu Kass's Artificial Data
## using all 4 variables
data(hbk)
pca < PcaHubert(hbk)
pca.distances(pca, hbk, rankMM(hbk))

Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.