similar to: correspondence analysis

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

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 ...

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

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

I'm experienced in statistics, but I am a first-time R user. I would like to use R for correspondence analysis. I have installed R (Mac OSX). I have used the package installer to install the CA package. I have run the following line with no errors to read in the data for a table: NonLuxury <- read.table("/Users/myUserName/Desktop/nonLuxury.data.txt") The R online help

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):

Trying to revive this old thread as problems continue. I have noticed from the gluster logs the following on m y volume called export: [2017-08-16 20:08:47.663908] I [MSGID: 109066] [dht-rename.c:1608:dht_rename] 0-export-dht: renaming /projects/ACTIVE/Automotive/JEEP/Brand Image Program June 2016/04_Western Region/Huntington Beach CDJR - Huntington Beach, CA/04 REVIT AND CAD/2017-08-16 CAD dwgs

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

Hi everybody, I am starting my friendship with R. Now I want to do a Correspondence Analysis using the vegan library or multiv library. Both give me the same results which differ from the ones I get running other programs like Statistica... I wounder if there is a problem with my matrix. I have cualitataive variable in the columns and sampling units in the rows... I import my matrix into R

Hi, a very basic question: What ist the easiest way in R to concatenate two lists of vectors? E.g, I have x<-list(c(1,2)) y<-list(c(3,4)) and I want to receive list(c(1,2),c(3,4)) thank you! Axel ________________________________________ Fraunhofer Institut fuer Arbeitswirtschaft und Organisation (IAO) Dipl. Inf. Axel Benz Nobelstr. 12 D-70569 Stuttgart Germany Tel. +49(0)7119702289 Fax.

Hi, I am about to write functions for multivariate kernel densitiy estimation with mixed categorical and continuous date (accoring to Jeff Racine and Qi Li), and the leave-one-out window esitmation needs a lot of computation. I am now optimizing the code performance and therefore fhe following questions: As R uses call-by-value for functions, is it computational expensive to pass large matrices

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

Hello, Dr. Viechtbauer. I am trying to perform a meta-analyis on a group of before-after studies using Metafor. I read your webpage including your correspondence with Dr. Dewey (https://stat.ethz.ch/pipermail/r-help/2012-April/308946.html), who also conducted a similar study. These information is very hepful, but I have one additonal question which I wonder if you can give me some instruction.

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

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

anacor-0.9.0 is on CRAN (by De Leeuw and Mair) anacor does correspondence analysis and canonical correspondence analysis. It can make row plots, column plots, joint plots, Benz?cri plots, regression plots, and transformation plots. Where appropriate, plots can be in 3d using either rgl or scatterplot3d. Row and column points can be in standard scaling, Benz?cri scaling, Goodman scaling,

anacor-0.9.0 is on CRAN (by De Leeuw and Mair) anacor does correspondence analysis and canonical correspondence analysis. It can make row plots, column plots, joint plots, Benz?cri plots, regression plots, and transformation plots. Where appropriate, plots can be in 3d using either rgl or scatterplot3d. Row and column points can be in standard scaling, Benz?cri scaling, Goodman scaling,

Full_Name: Axel Benz Version: 1.7.1 OS: Windows Submission from: (NULL) (137.251.33.43) This feature seems to be a basic bug: > 1=="1" [1] TRUE > as.numeric(1)=="1" [1] TRUE > as.numeric(1)==as.character("1") [1] TRUE isn't it necessary to distinguish beteen numbers and characters?? Best Regards, Axel

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]]

Hi, Win95 version, trying to build multiv. Following error (no mention in faq etc, but someone may have mentioned it recently). Appreciate any help. ------- Building multiv.dll from multiv.a -------- echo LIBRARY multiv > multiv.def echo EXPORTS >> multiv.def nm multiv.a | sed -n "/^........ [DT] _/s/^........ [BCDRT] _/ /p" >> multiv.def gcc -mdll