mv.calout.detect {parody} | R Documentation |
interface to a parametric multivariate outlier detection algorithm
mv.calout.detect(x, k = min(floor((nrow(x) - 1)/2), 100), Ci = C.unstr, lamfun = lams.unstr, alpha = 0.05, method = c("parametric", "rocke", "kosinski.raw", "kosinski.exch")[1], ...)
x |
data matrix |
k |
upper bound on number of outliers; defaults to just less than half the sample size |
Ci |
function computing Ci, the covariance determinant ratio
excluding row i. At present, sole
option is C.unstr (Caroni and
Prescott 1992 Appl Stat). |
lamfun |
function computing lambda, the critical values for Ci |
alpha |
false outlier labeling rate |
method |
string identifying algorithm to use |
... |
reserved for future use |
bushfire is a dataset distributed by Kosinski to illustrate his method.
a list with components
inds |
indices of outlying rows |
vals |
values of outlying rows |
k |
input parameter k |
alpha |
input parameter alpha |
VJ Carey
data(tcost) mv.calout.detect(tcost) data(bushfire) mv.calout.detect(bushfire)