AFC simple - R & Statistiques L'analyse factorielle des correspondances simple (AFCs), est une méthode exploratoire d'analyse des tableaux de contingences. Un tableau de contingences est un tableau croisant 2 variables qualitatives et contenant des effectifs. Par exemple, sur la population française, on peut croiser les catégories socio-professionnelles des personnes avec leur mode de départ en vacances. Pour télécharger les supports de formation : - rappel sur la décomposition du khi2 : Rafcs-khi2.pdf - introduction à l'AFC simple : Rafcs-rappels.pdf - effectuer des AFC simples avec R : Rafcs.pdf Posté le 15 février 2010 dans Analyses multivariées |
R Graphical Manual RExcelInstaller-package {RExcelInstaller} R Documentation Description The Excel add-in RExcel allows to transfer data between R and Excel, writing VBA macros using R as a library for Excel, and calling R functions as worksheet function in Excel. The package RExcelInstaller itself only serves as installer for Excel add-in(s). Once the appropriate add-in is installed, it is not necessary to load the package any more. To server its purpose, the installer downloads a Windows installer program from the site rcom.univie.ac.at and runs it. All the documentation for RExcel is available from the RExcel Help item in the RExcel menu which is installed in Excel. In Excel 2003 and earlier, the menu is placed on the main Excel menu bar , in Excel 2007 it can be found on the Add-Ins Ribbon . Details Package: RExcelInstaller Type: Package Version: Date: License: The easiest way to run RExcel is with R installed on the same machine as Excel. RExcel can also be used with a remote server. Author(s) References See Also
Rtips. Revival 2012! Paul E. Johnson <pauljohn @ ku.edu> The original Rtips started in 1999. It became difficult to update because of limitations in the software with which it was created. You are reading the New Thing! The first chore is to cut out the old useless stuff that was no good to start with, correct mistakes in translation (the quotation mark translations are particularly dangerous, but also there is trouble with ~, $, and -. (I thought it was cute to call this “StatsRus” but the Toystore’s lawyer called and, well, you know…) If you need a tip sheet for R, here it is. This is not a substitute for R documentation, just a list of things I had trouble remembering when switching from SAS to R. Heed the words of Brian D. 1.1 Bring raw numbers into R (05/22/2012) This is truly easy. myDataFrame <- read.table(‘‘myData’’,header=TRUE) If you type “? Suppose you have tab delimited data with blank spaces to indicate “missing” values. myDataFrame<-read.table("myData",sep="\t",na.strings=" ",header=TRUE) Step 1. or ?
Cours Programmation R R est à la fois un logiciel de statistique et un langage de programmation. R est un logiciel de traitement statistique des données. Il fonctionne sous la forme d'un interpréteur de commandes. Il dispose d'une bibliothèque très large de fonctions statistiques, d'autant plus large qu'il est possible d'en intégrer de nouvelles par le système des "packages", des modules externes compilés (sous forme de DLL sous Windows) que l'on peut télécharger gratuitement sur internet. R est un langage de programmation (de script) interprété dérivé de S (disponible dans le logiciel S-PLUS). Au fil des années, R sera de plus en plus incontournable dans le traitement exploratoire et statistique des données. Cet enseignement est avant tout un cours de programmation. Ce cours est dispensé en M2 Statistique et Informatique (SISE). Ricco Rakotomalala – Université Lyon 2
Apache Hadoop Apache Hadoop is an open-source software framework for storage and large-scale processing of data-sets on clusters of commodity hardware. Hadoop is an Apache top-level project being built and used by a global community of contributors and users.[2] It is licensed under the Apache License 2.0. The Apache Hadoop framework is composed of the following modules: Hadoop Common – contains libraries and utilities needed by other Hadoop modulesHadoop Distributed File System (HDFS) – a distributed file-system that stores data on commodity machines, providing very high aggregate bandwidth across the cluster.Hadoop YARN – a resource-management platform responsible for managing compute resources in clusters and using them for scheduling of users' applications.Hadoop MapReduce – a programming model for large scale data processing. Apache Hadoop is a registered trademark of the Apache Software Foundation. History[edit] Hadoop was created by Doug Cutting and Mike Cafarella[5] in 2005. Architecture[edit]
knitr: Elegant, flexible and fast dynamic report generation with R | knitr Overview The knitr package was designed to be a transparent engine for dynamic report generation with R, solve some long-standing problems in Sweave, and combine features in other add-on packages into one package (knitr ≈ Sweave + cacheSweave + pgfSweave + weaver + animation::saveLatex + R2HTML::RweaveHTML + highlight::HighlightWeaveLatex + 0.2 * brew + 0.1 * SweaveListingUtils + more). This package is developed on GitHub; for installation instructions and FAQ’s, see README. This website serves as the full documentation of knitr, and you can find the main manual, the graphics manual and other demos / examples here. Motivation One of the difficulties with extending Sweave is we have to copy a large amount of code from the utils package (the file SweaveDrivers.R has more than 700 lines of R code), and this is what the two packages mentioned above have done. Features The ideas are borrowed from other packages, and some of them are re-implemented in a different way (like cache). Misc
Connecting to a MongoDB database from R using Java It would be nice if there were an R package, along the lines of RMySQL, for MongoDB. For now there is not – so, how best to get data from a MongoDB database into R? One option is to retrieve JSON via the MongoDB REST interface and parse it using the rjson package. - and saved it to a database named citeulike in a collection named articles, you can fetch the first 5 articles into R like so: That works, but you may not want to use the MongoDB REST interface: for example, it may be slow for large queries or there might be security concerns. MongoDB has both C and Java drivers. Not to be deterred, I took the approach that has served me well my whole professional life: wing it, using what I could glean from Google searches and the Web. 1. 2. The Java class files are located in com/mongodb. 3. Next, I added the MongoDB classes to the classpath: The next step was to consult the MongoDB Java tutorial and try to figure out how to convert “normal” Java syntax to rJava. You get the idea. Success!
Software - Miquel De Cáceres Ainsa Indicspecies R package Indicator species are species that are used as ecological indicators of community or habitat types, environmental conditions, or environmental changes. In order to determine indicator species, the characteristic to be predicted is represented in the form of a classification of the sites, which is compared to the patterns of distribution of the species found in that set of sites. 'Indicspecies' is an R package that contains a set of functions to assess the strength of relationship between species and a classification of sites. As such, it includes the well-known IndVal method (Dufrêne & Legendre 1997) and extends it by allowing the user to study combinations of site groups (De Cáceres et al. 2010). Download indicspecies (ver. 1.6.7) from CRAN. Authors: Miquel De Cáceres, Florian Jansen Classifications of vegetation provide a way of summarizing our knowledge of vegetation patterns. Resniche R package Authors: Miquel De Cáceres STI R package Beals smoothing R functions