The help page says covmat: A covariance matrix, or a covariance list as returned by 'cov.wt'. Of course, correlation matrices are covariance matrices.
and there is an example of a covariance list (ability.cov). > factanal(factors = 2, covmat = ability.cov) > factanal(factors = 2, covmat = ability.cov$cov) both work. See > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. as we have no idea what you tried. On Tue, 6 Feb 2007, Alistair Campbell wrote: > Hi, > > I have a set of covariance matrices but not the original data. I want to > carry out some exploratory factor analysis. So, I am trying to construct > a covariance matrix list as the input for factanal. I can construct a > list which includes the cov, the centers, and the n.obs. But it doesn't > work. I get an error that says "Error in sqrt(diag(cv)) : Non-numeric > argument to mathematical function". So, obviously I am doing something > wrong. > > Two questions occur. Can someone either tell me how to construct a > proper covmat list object or point me to a description of how to do it? > The other question is whether it is possible to simply use the > covariance matrix as the argument for covmat in factanal? The > description implies that it is but I really have no idea of how to do > this. I have tried simply making covmat the covariance matrix but it > doesn't wotk. I just get the message "'covmat' is not a valid covariance > list" > > Anyway, thanks for any thoughts you might have on this. > > Alistair Campbell > -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ R-help@stat.math.ethz.ch 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.