Hello, unfortunately I can not find the pcaMethods package.
Birgit Am 26.11.2007 um 16:26 schrieb Kevin Wright: > The pcaMethods package offers a collection of different algorithms for > PCA, some of which (NIPALS and others) can be used on data that have > missing values. > > Kevin Wright > > > On Nov 24, 2007 4:59 PM, Hartmut Oldenbürger <[EMAIL PROTECTED]> > wrote: >> Hi Birgit, and All >> >> Possibly you should not consider the case completed ;-) >> There is an important alternative to imputing means, or estimates >> from >> first or second order >> regression (Frane, Psychometrica, BMDP): partial-least-squares >> (Wold), >> which uses as much >> information from the data as possible to estimate the principal >> components, or the missing data. >> >> Stephane Dray, also from Lyon, provides 'nipals' here: >> http://biomserv.univ-lyon1.fr/~dray/software.php >> There is also an interesting paper. - In case, you use PLS to >> estimate >> and impute, set the >> number of factors as high as reasonably possible, e.g. m-1, when m is >> the number of variables. >> best - Hartmut >> Oldenbürger >> --- >> [EMAIL PROTECTED] >> http://www.wipaed.wiso.uni-goettingen.de/~holdenb1 >> >> >> ______________________________________________ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide http://www.R-project.org/posting- >> guide.html >> and provide commented, minimal, self-contained, reproducible code. >> Birgit Lemcke Institut für Systematische Botanik Zollikerstrasse 107 CH-8008 Zürich Switzerland Ph: +41 (0)44 634 8351 [EMAIL PROTECTED] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
