Thanks a lot! Indeed, both implementations agree on the 'best' points. Your answer helped me a great deal.
Rainer > The two implementations use different consistency factors as well as > different small sample correction factors. > > 1. The search parts of both implementations produce the same result - > compare rrcov.mcd$best and mass.mcd$best. > > 2. The raw MCD covariance matrix is corrected as follows: > > MASS: > - Rousseeuw and Leroy (1987), p.259 (eq. 1.26) > - Marazzi (1993) (or may be Rousseeuw and van Zomeren (1900) p.638 (eq > A.9) > > rrcov: > - Croux and Haesbroeck (1999), Pison et.al. p. 337 > - Pison et.al. (2002), p.338 > > 3. The reweighted (final) covariance matrix is corrected as follows: > > MASS: no correction > rrcov: Pison et.al. (2002) p. 339 > > This explains the different covariance matrices. > As far as the location is concerned, in this particular case the raw MCD > estimates in MASS identify one additional outlier - observation 53, which > is > discarded from the computation of the reweighted estimates. > Look at the following plots and judge yourself if this is an outlier or > not: > > covPlot(hbk, mcd=rrcov.mcd, which="distance", id.n=15) > covPlot(hbk, mcd=mass.mcd, which="distance", id.n=15) > > valentin > -- GMX im TV ... Die Gedanken sind frei ... Schon gesehen? Jetzt Spot online ansehen: http://www.gmx.net/de/go/tv-spot ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
