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Hello. I have a data base with 50 qualitative variables and a lot of individuals. I try to estimate the links between one of these variables (landcover) and the 49 others (geomorphology, hydrography...). I want to use a "discriminant analysis on qualitative variables" (as DISQUAL in SPAD) or a " log-linear model ". Which R-Package(s) or other methods can you advise me.

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

Hello, I not have attached in this e-mail the zipped list of matrices I am using because it has 1 meg once zipped and anyway we cannot send attached files on r-help mailling list. First, after running the code that is written bellow, I realized that the printout of dudi.pca gives me for both of my matrices $cw length that are unequal to either respective $rank or $eig lengths. Is that

Dear all, I'm having difficulty getting the procedure for discriminant analysis. How can I specify the forward or backward stepwise analyses of variables into the model? I'm using lda in MASS and discrimin (ade4). I run R version 1.9.1. Thanks, Rog??rio

- This mail is in HTML. Some elements may be ommited in plain text. - WorldCIST Conference WorldCIST'15 - 3rd World Conference on Information Systems and Technologies, to be held at Ponta Delgada, S?o Miguel, Azores, Portugal, 1 - 3 April 2015, is a global forum for researchers and practitioners to present and discuss the most recent innovations, trends, results, experiences and concerns in

- This mail is in HTML. Some elements may be ommited in plain text. - WorldCIST Conference WorldCIST'15 - 3rd World Conference on Information Systems and Technologies, to be held at Ponta Delgada, S?o Miguel, Azores, Portugal, 1 - 3 April 2015, is a global forum for researchers and practitioners to present and discuss the most recent innovations, trends, results, experiences and concerns in

- This mail is in HTML. Some elements may be ommited in plain text. - -------------------------------------------------------------------- WorldCIST'15 Workshops Azores, April 1-3, 2015 http://www.aisti.eu/worldcist15/index.php/workshops -------------------------------------------------------------------------------- WorldCIST'15 WorldCIST'15 - 3rd World Conference on Information

- This mail is in HTML. Some elements may be ommited in plain text. - -------------------------------------------------------------------- WorldCIST'15 Workshops Azores, April 1-3, 2015 http://www.aisti.eu/worldcist15/index.php/workshops -------------------------------------------------------------------------------- WorldCIST'15 WorldCIST'15 - 3rd World Conference on Information

Decision Development Inc is currently hiring part-time employees or college interns to support our analytical division. Applications for the Assistant Marketing Research Analyst position will be given immediate consideration. Assistant Marketing Research Analysts work to structure, tabulate, and clean the data generated during our marketing research interviews. They form the foundation of an

RDQA is a package for Qualitative Data Analysis built upon R. It works both on the Windows and Linux/FreeBSD platforms. RQDA is an easy-to-use tool to assist in the analysis of textual data. At the present, it supports only plain text format data. All the information is stored in SQLite database via the R package of RSQLite. The GUI is based on RGtk2, via the aid of gWidgetsRGtk2. It includes a

RDQA is a package for Qualitative Data Analysis built upon R. It works both on the Windows and Linux/FreeBSD platforms. RQDA is an easy-to-use tool to assist in the analysis of textual data. At the present, it supports only plain text format data. All the information is stored in SQLite database via the R package of RSQLite. The GUI is based on RGtk2, via the aid of gWidgetsRGtk2. It includes a

All, I'm relatively new to using R, having used it thus far for some simple statistics and plotting. However, I'm not new to programming by any measure. I've been looking at the various modules available for clustering, factor analysis, etc. and find that I need advice on which modules I should be focusing on and their application. I have a data set comprised of columns of both

Hello, I'm a R newcomer and I'm wondering the kind of data structure that would best fit to my problem: my data are equities (stocks) : so I have a time serie (say 1 year of weekly data), and a bunch of qualitative + quantitative variables : the sector of the stock (biotech/finance...), the geographical region, the name, ISIN code, P/E ratios, whatever... The data.frame is perfect for the

Hi! Apologies if this is not the correct place to ask. I am attempting a MFA analysis of a dataset based on wine chemical and sensory analysis, based on the STHDA tutorial [1]. (I am using this dataset here too, as an example dataset to work on without posting my actual data. I've tried this with both my data and the example data, with the exact same results.) The only issue I am having is

Dear all, RQDA is a package for computer-aided qualitative data analysis, currently supporting plain text as qualitative data. It supports various operations in the grounded theory tradition such as coding, retrieval of codings, categorisation, attributes etc. It can also be used for content analysis and similar analysis, the result of which can be exported to be analysed in quantitative or

Dear all, RQDA is a package for computer-aided qualitative data analysis, currently supporting plain text as qualitative data. It supports various operations in the grounded theory tradition such as coding, retrieval of codings, categorisation, attributes etc. It can also be used for content analysis and similar analysis, the result of which can be exported to be analysed in quantitative or

Hi Gavin, I can't work through this right now, but I would start by looking at the 'hetcor' package to get the correlations, or if they are already in the return object, build a plot from these. Jim On Wed, Feb 22, 2023 at 4:24 AM gavin duley <gduley at gmail.com> wrote: > > Hi! > > Apologies if this is not the correct place to ask. I am attempting a > MFA

Hello, My name is Dontrece Smith. I am creating figures for my GAMs. I change my qualitative variables to 1 or 2 in my dataset, so I would be able to run my GAMs. However, R will only display plots for my quantitative variables and not my qualitative variables. Is there any way to fix this issue? I listed some of my code below: > library(mgcv) This is mgcv 1.7-13. For overview type

I am using the read.table function to load an Excel data set into R. It has a few variables with very long qualitative (free response typically in sentences) response that I would like to keep, but would like to limit the "length" of the response that R shows. Is there some sort of string or column width command I can include in the read.table function to limit the length of words used

I've found RColorBrewer useful for its qualitative palettes, but wished that it could generate more than 12 qualitative palettes (e.g. with Set3). Any suggestions for alternative color palette generators that can handle e.g. 18 distinctive colors? (I'm aware of using rainbow(), but this doesn't generate enough distinct colors when the number of palettes is large). Thanks, Andrew