[R] Discriminant Correspondence Analysis
ehlers at ucalgary.ca
Wed Dec 15 09:20:25 CET 2010
On 2010-12-14 23:48, Wayne Sawtell wrote:
> 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.
See page 5 of 'An Introduction to R'. I don't want to sound too
pedantic but I strongly recommend that you (at least) work the
whole of the intro session in Appendix A.
> 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
Discriminant analysis works with 'classes' (as you did quote in
your original mail). What do you consider to be your classes?
> 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,
This is almost always a bad (although usually harmless) idea. Why
not use the words?
> 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?
Perhaps it's time to find a local statistical consultant?
> thanks again and sorry if my question is too long
> On 14 December 2010 18:39, Peter Ehlers <ehlers at ucalgary.ca
> <mailto:ehlers at ucalgary.ca>> wrote:
> 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
> 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
> 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
> 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
> 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
> saying that the program cannot find the "discrimin.coa" command.
> discrimin.coa(df, fac, scannf = TRUE, nf = 2)
> 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
> nf if scannf FALSE, an integer indicating the number of kept axes
> 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
> and Cluster Analysis in another program (PAST) in order to see
> if the data
> fall into distinct groupings that might represent different
> 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
> Thanks for any help offered on any of these points.
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