Enio Jelihovschi" eniojelihovs@gmail.com Date: Fri, 20 Oct 2006 11:28:12 -0200 Subject: CORRESPONCE ANALYSIS Dear All I am new R user, trying to do correspondence analysis using the function mca of the package MASS. My question is: In the following example farms.mca <- mca(farms, abbrev = T) # Use levels as names plot(farms.mca, cex = rep(0.7, 2), axes = F) How can I change the "plot" so that each factor would get a different colour, in order to enhance the visualization of the patterns. Thank you, for any tip in that direction. Enio Jelihovschi [[alternative HTML version deleted]]
On 2006-10-20 19:48, Enio Jelihovschi wrote:> Enio Jelihovschi" eniojelihovs at gmail.com > Date: Fri, 20 Oct 2006 11:28:12 -0200 > Subject: CORRESPONCE ANALYSIS > Dear All > I am new R user, trying to do correspondence analysis using the function mca > of the package MASS. My question is: In the following example > > farms.mca <- mca(farms, abbrev = T) # Use levels as names > > plot(farms.mca, cex = rep(0.7, 2), axes = F) > How can I change the "plot" so that each factor would get a different > colour, in order to enhance the visualization of the patterns.Is this what you want: text(farms.mca$cs, labels = dimnames(farms.mca$cs)[[1]], cex = 0.7, col = rep(2:5, c(4, 4, 3, 5))) ? HTH, Henric> Thank you, for any tip in that direction. > Enio Jelihovschi > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at 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. >
Dear All, I am in the process of teaching myself R and am getting the hang of it slowly, and so apologies for what may be a novice question. (Many thanks to those who have helped me so far). I have been performing "normal" Correspondence Analysis for a number of years using a variety of packages. CA is available in a number of R packages (e.g. vegan). Could anyone advise me which one(s) would provide me with the "standard" Greenacre diagnostic statistics (ie. quality, mass, contribution etc as discussed in Correspondence Analysis in Practice, esp. chapter 11) and how I get hold of them? Many thanks in advance, Kris Lockyear. _________________________________________________________________ Be the first to hear what's new at MSN - sign up to our free newsletters!