similar to: Newbie Correspondence Analysis Question

Displaying 20 results from an estimated 1000 matches similar to: "Newbie Correspondence Analysis Question"

2010 Sep 26
4
How to update an old unsupported package
Hi all, I have a package that is specific to a task I was repetitively using a few years ago. I now needed to run it again with new data. However I am told it was built with an older version or R and will not work. How can I tweak the package so it will run on 11.1? It was a one-off product and has not been maintained. Is there a way to "unpackage" it and repackage it to work? I
2004 Jun 22
1
Need for advise for Correspondence Analysis
Dear R users, I m quite a novice in using R for factor analysis and I would need some help to choose the right function. I have a contingency table and I would like to perform a Correspondence analysis on this table, followed by a hirarchical clustering of my variables projected in on the first principal components. Here are my question : - what is the more appropriate function to do so ...
2007 Jun 06
1
correspondence analysis
Hello, I am new to R and I have a question about the difference between correspondence analysis in R and SPSS. This is the input table I am working with (4 products and 18 attributes): > mytable 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 1 15 11 20 4 14 7 1 2 1 4 12 12 17 19 11 20 9 10 2 19 18 14 14 16 4 14 11 11 15 22 19 22 16 21 19 15 16 3 16 13 10 9 15 4 10 7 11 13 18
2010 Sep 26
1
Storing CA Results to a Data Frame?
[Sorry- somehow the first time I posted this it got attached to another thread -Vik] I am successfully performing a correspondence analysis using the commands: NonLuxury <- read.table("/Users/myUserName/Desktop/nonLuxury.data.txt") ca(NonLuxury) I would like to store the results to a data frame so that I can write them to disk using write.table. I have tried
2000 Nov 11
2
problem using MASS corresp and mca functions
Hello, I'm an absolute beginner with R and neophite in data analysis, so please bear with me if I ask stupid question. I'm trying to do a correspondence analysis using R and MASS corresp function, but I get an error message which I'm unable to interpret: > data(weblog) > library(MASS) > corresp(~ url + fromurl, data=weblog) Error in svd(t(t(x1 * Dr) * Dc)) : error 306 in
2001 Mar 02
0
[OT] correspondence analysis w/ non-mutually-exclusive ca tegories
Andy, Take a look at Greenacre, Theory and Applications of Correspondence Analysis. He has many example of dealing with all sorts of data. Basically, the technique is relevant for 2-way tables -- MCA is an extenstion. It is not clear in your example whether CA is really appropriate -- you want to make an observation (if at all possible) fall in one cell, treating the others layers as
2001 Mar 01
1
[OT] correspondence analysis w/ non-mutually-exclusive categories
Greetings, again. This is not strictly an R question, so please feel free to ignore it if you like. My question is about the substance of correspondence analysis. Specifically, is it appropriate to use ca on a matrix of values such that the columns and/or rows are not mutually exclusive? To be more detailed: - The standard use of ca is illustrated in the example of corresp() (from MASS):
2011 Feb 05
1
different results in MASS's mca and SAS's corresp
Dear list: I have tried MASS's mca function and SAS's PROC corresp on the farms data (included in MASS, also used as mca's example), the results are different: R: mca(farms)$rs: 1 2 1 0.059296637 0.0455871427 2 0.043077902 -0.0354728795 3 0.059834286 0.0730485572 4 0.059834286 0.0730485572 5 0.012900181 -0.0503121890 6
2000 Dec 12
0
correspondence analysis
Hello, I'm trying to do some correspondence analyis, with R, of course (by correspondence analysis, I'm refering to JP Benz?cri's methods, in case there might be some other thing with a similar name) I've found a couple of tools refering to C.A in the existing packages : ca() in package multiv and corresp()/mca() in MASS. MASS tools look more easy to use (it is supposed to put
2005 Jun 09
3
plot(corresp(data)...)
hi, My code: data<-matrix(data=c(0.425,0.5,0.75,0.125,0.25,0.475,0.375,0.25,0.625,0.5,0.1,0.125,0,0.25,0.25),nrow=3,ncol=5,byrow=TRUE, dimnames=list(c("Good","Medium","Bad"),c("Content","Logistic","Trainer","Supply","User contribution"))) plot(corresp(data,nf=2),xlim=c(-1,1),ylim=c(-1,1)); The plot is
2006 Jul 20
3
Correspondence analysis with R
Hello everybody, i'm having some trouble performing correspondence analysis with R for Mac OS X. Does anyone know about some useful package? And also, if i had found coordinates of points representing row and column profiles, how do i put them in a single figure with labels identifying each one of them? This thing is getting me almost crazy... Thank you in advance for answering, bye
2005 May 25
1
plot 3D
Is it possible to do a graphic in 3D? This is my source: but this one is on 2D and at moment variables put on other variables, so it is difiicult to differentiate them visibly. plot(corresp(data,nf=2),xlim=c(-1,1),ylim=c(-1,1)); Thanks Sabine --------------------------------- ils, photos et vidéos ! [[alternative HTML version deleted]]
2001 Feb 16
12
canonical correspondence analysis
Is there an R function that does canonical correspondence analysis. Can it be done using the VR function corresp()? If not, how hard it be to write R code to do it? I am a population biologist with long but patchy programming experience in C, Smalltalk, Java and other languages. Thanks, Patrick Foley patfoley at csus.edu
2012 Jun 05
2
Good Decision Trees with Product Purchased Data?
A client has inquired about producing a decision tree from data which could include: - ID of brand purchased - Importance ratings (1-10 scale) for a number of relevant attributes (price, strength, recommended by a friend, etc.) In other words, a rating of how important each attribute is in the decision as to which brand to purchase. I've just run a test decision tree using the closest thing
2003 Mar 10
1
ylim in plot(corresp(,df=2))
Hi! If I do: plot(corresp(a, nf = 2),xlim=c(-1,2),ylim=c(-1,1)) while the xlim takes effect, the ylim does not, no matter the values given for ylim. Is this intentional? is this an error? (I think this might be related with line 41 in biplot.default in mva) (using R 1.6.2 on a linux (suse 7.3) box.) Thanks Agus Dr. Agustin Lobo Instituto de Ciencias de la Tierra (CSIC) Lluis Sole Sabaris
2003 Jan 17
2
Methods package is now attached by default
The current r-devel (aka R 1.7.0) now attaches the package "methods" by default at startup. A new option, "defaultPackages", is set to c("methods", "ctest") by default, causing the .First in package base to require those two packages at startup. There are two main known differences from having methods attached: - the definition of class() changes, in
2012 Apr 03
5
process_sdp: Multiple audio streams are not supported
Hello folks, I'm running 1.8.11 on a Centos 6 system with an adjacent Hylafax server using softmodems: Noticed this in the Asterisk log when trying to send a fax from Hylafax to Asterisk: [Apr 3 01:53:09] WARNING[29184]: chan_sip.c:8926 process_sdp: Multiple audio streams are not supported I've googled a few asterisk tickets that may suggest that yes, multiple audio streams are not
2002 Aug 27
5
rsync: push_dir TESTDIR: No such file or directory
Hi all. I'm getting the following error when using rsync: nice -n 20 rsync -e "ssh -p30000" --recursive --verbose --verbose --checksum --times --modify-window 2 --port=31000 --dry-run /cygdrive/f/bkp/Doc/Builds/Buildsheets/ MYUSERNAME@MY.SERV.ER.IP:TESTDIR opening connection using ssh -p30000 -l MYUSERNAME MY.SERV.ER.IP rsync --server -vvntrc --modify-window=2 . TESTDIR
2014 Feb 08
4
force group does not work
Hi I set up a samba 4.1.4 server on the latest FreeBSD RELEASE 10. Unfortunately it doesn't seem to consider the option force group. After hours ofresearch I couldn't figure out what I'm still missing. unix extensions is set to no. Setting the debug level up to 10 also didn't help ;( Is this a bug or is there simply a mistake in my setup? When *valid users = @Groupname* is
2006 May 06
2
How to test for significance of random effects?
Dear list members, I'm interested in showing that within-group statistical dependence is negligible, so I can use ordinary linear models without including random effects. However, I can find no mention of testing a model with vs. without random effects in either Venable & Ripley (2002) or Pinheiro and Bates (2000). Our in-house statisticians are not familiar with this, either,