Thank you all for the advice. I have looked through the Introduction to R pdf and got some pointers but when I try to implement them it does not work. If someone could clarify a couple of basic things, I would appreciate it.
When I successfully read in my file, the prompt changed from > to +. Then when I typed in the suggested commands, nothing happened. For the discrimin.coa command, the only part I don't understand is what to put for "fac". Is this the grouping variable that I obtained from my Principal Co-ordinates Analysis? My goal, by the way, is to test whether the groups into which PCoA put my data are valid. The data consist of specimen measurements and categorical observations. So I have a rectangular table of data with headings (names of measured characters) at the top of each column of numbers. This is a sample: X1 X2 X3 X4 X5 0.123 0.854 0.319 1 2 0.562 0.472 0.917 0 1 0.381 0.285 0.146 2 1 where X4 is a body shape character, which I've converted to numbers, instead of words (0 - round, 1 - oblong, 2 - rectangular). I've included X5, which is just the column in which I entered the group number into which PCoA grouped the data points or rows (each row represents a different specimen that was measured according to the characters in the headings). So, should I put "fac = X5"? Is that how Discriminant Correspondence Analysis works? thanks again and sorry if my question is too long Wayne On 14 December 2010 18:39, Peter Ehlers <ehl...@ucalgary.ca> wrote: > Wayne, > > So far, no one has said the obvious: > Please do work your way through (or at least > skim) "An Introduction to R" which you'll > find right there on your computer under > Help/Manuals. Your questions indicate that > you have not yet done so. Do it, it really > will pay off. > > Peter Ehlers > > > On 2010-12-14 12:36, Wayne Sawtell wrote: > >> Hello everyone, >> >> I am totally new to the R program. I have had a look at some pdf documents >> that I downloaded and that explain how to do many things in R; however, I >> still cannot figure out how to do what I want to do, which is to perform >> Discriminant Correspondence Analysis on a rectangular matrix of data that >> I >> have in an Excel file. I know R users frown upon Excel and recommend >> converting Excel files to .csv format, which I have done, no problem. That >> is not an issue. >> There are several parts to my problem. >> 1) When I try the read.table command, even if I include the directory name >> in the filename, R still cannot read the file, even if it is in .csv >> format >> 2) I was able to copy my file and then read the clipboard contents into R >> but then I do not know to assign a name to the data frame in order to >> conduct any operations on it >> 3) I need the ADE4 program in order to perform Discriminant Correspondence >> Analysis, so I used the "install.packages" command to install it. It >> installed no problem but I do not know how to access the ADE4 program in >> R. >> I am unable to open it directly, either. >> 4) I thought that using the ADE4 GUI (called "ade4TkGUI") would be easier >> because I do not know many of the R commands; but, again, I downloaded it >> but cannot open or access it. >> >> The following is the suggested coding that I found through the R website, >> but when I try to use this code, I don't know how to assign a name for the >> df, or what to put for "fac", and what is worse, I get an error message >> saying that the program cannot find the "discrimin.coa" command. >> >> >> Usage >> >> discrimin.coa(df, fac, scannf = TRUE, nf = 2) >> >> Arguments >> >> df a data frame containing positive or null values >> >> fac a factor defining the classes of discriminant analysis >> >> scannf a logical value indicating whether the eigenvalues bar plot should >> be >> displayed >> >> nf if scannf FALSE, an integer indicating the number of kept axes >> >> Examples >> >> data(perthi02) >> >> plot(discrimin.coa(perthi02$tab, perthi02$cla, scan = FALSE)) >> For clarification, my data consists of measurements of morphological >> characters of an assemblage of biological specimens. I have already >> performed Principal Co-ordinates Analysis, Principal Compionents Analysis >> and Cluster Analysis in another program (PAST) in order to see if the data >> fall into distinct groupings that might represent different morphological >> species. I now want to test the groupings that I found on my test data set >> using Discriminant Correspondence Analysis.There are both continuous and >> categorical characters, which is the reason why I need to perform >> Discriminant Correspondence Analysis, instead of Linear Discriminant >> Analysis, which is only valid for continuous measurements. R seems to be >> the >> only program in which I can perform Discriminant Correspondence Analysis. >> >> Thanks for any help offered on any of these points. >> Wayne >> >> [[alternative HTML version deleted]] >> >> >> ______________________________________________ >> 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. >> > > [[alternative HTML version deleted]] ______________________________________________ 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.
