I’ll be running an R course soon and I am looking for fun (public) datasets to use in data manipulation and visualization. I would like to use a single dataset that has some easy variables for the first days, but … Continue reading →

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...

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

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...

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 →

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...

Data analyses are the product of many different tasks, and statistical methods are one key aspect of any data analysis. There is a common workflow in the related areas of informatics, data mining, data science, machine learning, and statistics. The workflow tasks include data preparation, the development of predictive mathematical models, and the interpretation and Read More ...The...

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)...

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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