Re: [R] Discriminant Correspondence Analysis
See inline. 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? Peter Ehlers thanks again and sorry if my question is too long Wayne On 14 December 2010 18:39, Peter Ehlers ehl...@ucalgary.ca mailto: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
Re: [R] Discriminant Correspondence Analysis
On Wed, 2010-12-15 at 02:48 -0500, 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. That means that the commands you used to read in the file were syntactically incomplete. In such cases, R changes the prompt from `` to `+` indicating that the previous line(s) were incomplete and extra input is require. New useRs hit this problem very often, usually because they forgot to close quotes (in your case around the filename?) or perhaps a missing closing parenthesis ( `)` ). The former causes them no end of frustration because, of course, until one closes the quote, R thinks you are just typing in a long string. I would suggest your file was not read in correctly or even at all. Check you have matched quotes and parentheses. If you need, get a better text editor that will highlight code and match brackets to help you spot the errors. Tinn-R might be useful for you for example, on Windows. For the discrimin.coa command, the only part I don't understand is what to put for fac. Discriminants analysis finds linear combinations of variables that best separate your group means. I don't know discriminant CA but it will be doing something similar. The point is to find rules that predict the groups. So 'fac' is where you tell `discrimin.coa` what groups your data belong to, as a factor. Is this the grouping variable that I obtained from my Principal Co-ordinates Analysis? Doubt it - in what sense does PCoA estimate groups or clusters of samples? PCoA just extracts linear combinations of your variables that have maximal variance. It is a bit like PCA but using any dissimilarity matrix. I'm not familiar with PCoA being used to provide a grouping variable. My goal, by the way, is to test whether the groups into which PCoA put my data are valid. See the above; I doubt PcoA will be useful here. 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). Don't do that. Store this as a factor in R with the labels round, oblong etc. R will store these numerically in R as 1, 2, 3, etc but will display them with nice names so you don't have to remember what the codes mean. 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? Unlikely. You are going to have to remove 'X5' from the data that you pass as argument `df` and you can't refer to X5 directly like that without some extra efforts. You could try: discrimin.coa(DF[, -5], fac = as.factor(DF[, 5])) thanks again and sorry if my question is too long You seem to be missing a lot of the basics and also don't fully get the statistical methods you are using; a bad combination in my book. ADE4 is well documented, so check and run through the examples for some of the functions in the package to familiarise yourself with how things work. If you need specific help, there is an ade4 mailing list which is likely best placed for you to post your questions regarding use of functions in that package. Good luck, HTH G 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
Re: [R] Discriminant Correspondence Analysis
On 15/12/2010 9:36 a.m., 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. Actually one of the things we don't like about Excel is how it writes .csv files, so many R users find it much more reliable to read data directly from Excel files. In my case, the two major tools I use on Windows with great satisfaction are xlsReadWrite and RODBC. There are other suitable options if you are working on linux. For more comprehensive information see: http://rwiki.sciviews.org/doku.php?id=tips:data-io:ms_windows David Scott 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. -- _ David Scott Department of Statistics The University of Auckland, PB 92019 Auckland 1142,NEW ZEALAND Phone: +64 9 923 5055, or +64 9 373 7599 ext 85055 Email: d.sc...@auckland.ac.nz, Fax: +64 9 373 7018 Director of Consulting, Department of Statistics __ 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.
Re: [R] Discriminant Correspondence Analysis
Read files, if you're on windows remember to include the path like this: C:\\Documents and Settings\\USER\\My Documents\\MyFile.csv -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Wayne Sawtell Sent: Tuesday, December 14, 2010 12:36 PM To: r-help@r-project.org Subject: [R] Discriminant Correspondence Analysis 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. __ 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.
Re: [R] Discriminant Correspondence Analysis
Wayne, 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. Before you can use a package you have downloaded you need to activate it. There are different ways of doing this. Simplest is to type library(ade4). ## library(ade4) ?discrimin.coa Follow Bastiaan and read in your file as follows (single forward slashes also work): ## See ?read.csv as you may need to change some switches MyFile - read.csv(C:\\Documents and Settings\\USER\\My Documents\\MyFile.csv) str(MyFile) Without data it is difficult to help you further, but your general call to discrimin.coa is ## This may or may not work; depends what's in MyFile T.discrimin - discrimin.coa(MyFile, fac = someFacInMyFile, scann=F, nf=4) T.discrimin plot(T.discrimin) Regards, Mark. -- View this message in context: http://r.789695.n4.nabble.com/Discriminant-Correspondence-Analysis-tp3087929p3088091.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.
Re: [R] Discriminant Correspondence Analysis
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. __ 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.
Re: [R] Discriminant Correspondence Analysis
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
