A clarification - yes, calculating the pearson covariance does give the expected results. I dont fully understand why yet, but many thanks for this help!
2012/8/12 Boel Brynedal <bryne...@gmail.com>: > Thanks for these replies. > @Peter - are these methods only suitable for pearson covariances? That > would def explain my issues. Sorry for my ignorance, but I would > highly appreciate an explanation. My original covariance matrix is > calculated using spearman as well (which is suitable for the data). > @Michael - I am simulating a sample size of 20351* 8368 so I do not > think that the sample size is the issue here. > > 2012/8/12 peter dalgaard <pda...@gmail.com>: >> >> On Aug 11, 2012, at 16:17 , Boel Brynedal wrote: >> >>> cov8=cov(sample8,method='spearman') >> >> There's your problem. I'm surprised that nobody seems to have picked up on >> this, but Spearman covariances are of the ranks, not of the data. Try >> method="pearson". >> >> -- >> Peter Dalgaard, Professor, >> Center for Statistics, Copenhagen Business School >> Solbjerg Plads 3, 2000 Frederiksberg, Denmark >> Phone: (+45)38153501 >> Email: pd....@cbs.dk Priv: pda...@gmail.com >> >> >> >> >> >> >> >> ______________________________________________ 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.
