r project R-project

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R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R
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The R Blog
Build of R and CRAN Packages Tomas Kalibera 2020-07-30 New Features in the R Graphics Engine Paul Murrell 2020-07-15 Improvements to Clipping in the R Graphics Engine 2020-06 Tomas Kalibera 2020-05-29 UTF-8
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Survey analysis in R

Survey analysis in R This is the homepage for the “survey” package, which provides facilities in R for analyzing data from complex surveys. The current version is 3.29. A much earlier version (2.2) was published in Journal of Statistical Software An experimental
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R package FME

The project summary page at R-Forge. Download Documentation Manual and Tutorials The Reference Manual at CRAN (PDF of help-pages) Tutorial: Main package vignette Tutorial: Sensitivity, Calibration, Identifiability, Monte Carlo Analysis and MCMC of a
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R package simecol

Prerequisites simecol is based on R, a freely available system for statistical computation and graphics.Current versions are tested with R version 3.0 or above. simecol depends on the deSolve package for numerical integration. optional: the tcltk package is required
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Welcome to RQDA Project

Memos of documents, codes, coding, project, files and more Retrieval of coding, and easily return to the original file (to ease the problem of segmentation). Conditional retrieval is supported as well. Single-file (*.rqda) format, which is basically a SQLite database
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R package deSolve

deSolve Home Example Bibliography–> CRAN–> R-Forge
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R-INLA Project

R-INLA is a package in R that do approximate Bayesian inference for Latent Gaussian Models. This site is dedicated to that package and methodological developments that goes along with it.
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OOMPA is a suite of R packages for the analysis of gene expression (RNA), proteomics profiling , and other high throughput molecular biology data. All higher level analysis tools in OOMPA work with the expressionSet classes defined in BioConductor .
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R.projectは,地域と共に新しい人の流れをつくる會社です。 VIEW R.project が行っているプロジェクトとそれにまつわる物語 Project 01 サンセットブリーズ保田 (千葉県鋸南町) Project 02 アカデミーハウス館山
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R Package rPython

rPython R package This package allows the user to call Python from R. It is a natural extension of the rJython package by the same author.What can be done with it? rPython is intended for running Python code from R. R programs and packages can: Pass data to
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Chapman & Feit: R for Marketing Research and Analytics

Welcome to R for Marketing Research and Analytics Note, April 2019: The 2nd Edition of R for Marketing Research and Analytics was released this month. All code and exercises are posted here as .R files. We will update Exercise Notebooks in coming weeks (basic solutions in R code are available now).
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Welcome to the home page of the ESS project Emacs Speaks Statistics (ESS) is an add-on package for GNU Emacs . It is designed to support editing of scripts and interaction with various statistical analysis programs such as R, S-Plus, SAS, Stata and OpenBUGS/JAGS.
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R Markdown

Turn your analyses into high quality documents, reports, presentations and dashboards with R Markdown. Use a productive notebook interface to weave together narrative text and code to produce elegantly formatted output. Use multiple languages including R
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R-Forge: Vennerable: R Development Page

R Development Page Contributed R Packages Below is a list of all packages provided by project Vennerable. Important note for package binaries: R-Forge provides these binaries only for the most recent version of R, but not for older versions.
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 · The R-universe system Statistical Software Project Packages Category All Computing Infrastructure Data Access Data Extraction Data Publication Data Visualization Databases Geospatial HTTP tools Image & Audio Processing Literature Security Taxonomy
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Welcome to T-LoCoH!
Installation Installation from R-Forge (recommended) To install T-LoCoH, type one of the following commands below at the R console. If you get stuck, see the steps for manual installation. # Windows: install.packages(“tlocoh”, dependencies=TRUE, repos=c(“http