1703 search results for "rstudio"

100 “must read” R-bloggers’ posts for 2015

January 20, 2016
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100 “must read” R-bloggers’ posts for 2015

The site R-bloggers.com is now 6 years young. It strives to be an (unofficial) online news and tutorials website for the R community, written by over 600 bloggers who agreed to contribute their R articles to the website. In 2015, the site served almost 17.7 million pageviews to readers worldwide. In celebration to R-bloggers’ 6th birth-month, here are the top 100 most read R posts written...

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Shiny 0.13.0

January 20, 2016
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Shiny 0.13.0

Shiny 0.13.0 is now available on CRAN! This release has some of the most exciting features we’ve shipped since the first version of Shiny. Highlights include: Shiny Gadgets HTML templates Shiny modules Error stack traces Checking for missing inputs New JavaScript events For a comprehensive list of changes, see the NEWS file. To install the

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R trends in 2015 (based on cranlogs)

January 20, 2016
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It is always fun to look back and reflect on the past year. Inspired by Christoph Safferling's post on top packages from published in 2015, I decided to have my own go at the top R trends of 2015. Contrary to Safferling's post I'll try to also (1) look at packages from previous years that hit the big...

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miniCRAN – developing internal CRAN Repositories

January 19, 2016
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by Steph Locke Today, I needed to work on a package that had numerous dependencies on internal packages and ones from CRAN. To be able to handle dependencies in the installation process, I needed something like CRAN so that install.packages() … Continue reading →

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Formatting table output in R

January 19, 2016
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Formatting table output in R

Formatting data for output in a table can be a bit of a pain in R. The package formattable by Kun Ren and Kenton Russell provides some intuitive functions to create good looking tables for the R console or HTML quickly. The package home page demonstrates the functions with illustrative examples nicely.There are a few points I...

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Confidence Regions for Parameters in the Simplex

January 18, 2016
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Confidence Regions for Parameters in the Simplex

Consider here the case where, in some parametric inference problem, parameter  is a point in the Simplex, For instance, consider some regression, on compositional data, > library(compositions) > data(DiagnosticProb) > Y=DiagnosticProb-1 > X=DiagnosticProb > model = glm(Y~ilr(X),family=binomial) > b = ilrInv(coef(model),orig=X) > as.numeric(b) 0.3447106 0.2374977 0.4177917 We can visualize that estimator on the simplex, using > tripoint=function(s){ + p=s/sum(s)...

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Scheduling R Markdown Reports via Email

January 17, 2016
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Scheduling R Markdown Reports via Email

R Markdown is an amazing tool that allows you to blend bits of R code with ordinary text and produce well-formatted data analysis reports very quickly. You can export the final report in many formats like HTML, pdf or MS Words which makes it easy to sh...

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Nina Zumel and John Mount part of R Day at Strata + Hadoop World in San Jose 2016

January 17, 2016
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Nina Zumel and I are honored to have been invited to be part of Strata + Hadoop World in San Jose 2016 R Day organized by RStudio and O’Reilly. We have written a lot on the topic of model validation in R and we are very excited to distill it down to an exciting tutorial. … Continue reading...

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NBA Stat in a Shiny App

January 16, 2016
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IntroductionShiny app is a new way to present data interactively. Unlike methods like D3, shiny performs complex calculation in real time. As a result, shiny app is more powerful and versatile. However, this also means one cannot simply embed an interactive shiny app in an html document. It needs to be hosted on a shiny server. I rented one...

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RcppParallel: Getting R and C++ to work (some more) in parallel

January 15, 2016
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RcppParallel: Getting R and C++ to work (some more) in parallel

(Post by Dirk Eddelbuettel and JJ Allaire) A common theme over the last few decades was that we could afford to simply sit back and let computer (hardware) engineers take care of increases in computing speed thanks to Moore’s law. That same line of thought now frequently points out that we are getting closer and closer

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