Hi Gundala, >> Suppose I have 2 matrices A and B. >> And I want to measure how good each of this matrix is.
You really want to be using Robert & Escoufier's RV-coefficient (A unifying tool for linear multivariate statistical methods: The $RV$-coefficient Appl. Statist., 1976, 25, 257-265). Several packages in R use it. If I were you I would look at the coinertia() function in package ade4, which is a fine implementation, with a good plot method. There is also a randomization test. You could also look at Procrustean analysis (also with a randomization test and also implemented in the named package). HTH, Mark. Gundala Viswanath wrote: > > Hi all, > > Suppose I have 2 matrices A and B. > And I want to measure how good each of this matrix is. > > So I intend to compare A and B with another "gold standard" > matrix X. Meaning the more similar a matrix to X the better it is. > > What is the common way in R to > measure matrix similarity (ie. A vs X, and B vs X) ? > > > - Gundala Viswanath > Jakarta - Indonesia > > ______________________________________________ > 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. > > -- View this message in context: http://www.nabble.com/Measuring-Goodness-of-a-Matrix-tp18092757p18100047.html Sent from the R help mailing list archive at Nabble.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.
