396 search results for "shiny"

Incidental R

August 7, 2014
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Incidental R

by Joseph Rickert Last week, I posted a list of sessions at the Joint Statistical Meetings related to R. As it turned out, that list was only the tip of the iceberg. In some areas of statistics, such as graphics, simulation and computational statistics the use of R is so prevalent that people working in the field often don't...

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Predicting Monthly Car Sales for Brands in US: First Step

August 6, 2014
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I've set out to produce monthly forecasts of monthly car sales by brand in the US. So far I've made a SUTSE dynamic linear model (code on Github) and created a Shiny app (http://sweiss.shinyapps.io/carvis/) as a prototype (no predictions...

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Parameterized SQL queries

August 5, 2014
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Mateusz Żółtak asked me to spread the word about his new R package for parameterized SQL queries. Below you can find the copy of package vignette. If you work with SQL in R you may find it useful. Mateusz Żółtak The package RODBCext is an extension of the RODBC database connectivity package. It provides support

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Come see RStudio at JSM in Boston

August 1, 2014
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Come see RStudio at JSM in Boston

The Joint Statistical Meetings (JSM) start this weekend! We wanted to let you know we’ll be there. Be sure to check out these sessions from RStudio and friends: Sunday, August 3 4:00 PM: A Web Application for Efficient Analysis of Peptide Libraries: Eric Hare*+ and Timo Sieber and Heike Hofmann 4:00 PM: Gravicom: A Web-Based

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The R Markdown Cheat Sheet

August 1, 2014
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The R Markdown Cheat Sheet

R Markdown is a framework for writing versatile, reproducible reports from R. With R Markdown, you write a simple plain text report and then render it to create polished output. You can: Transform your file into a pdf, html, or Microsoft Word document—even a slideshow—at the click of a button. Embed R code into your report. When

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A Data Scientist’s and R User’s Guide to the JSM

July 31, 2014
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by Joseph Rickert The Joint Statistical Meetings (JSM) get underway this weekend in Boston and Revolution Analytics is again proud to be a sponsor. More than 6,000 statisticians and data scientists from around the world are expected to attend and listen to thousands of presentations. It is true that many talks will be on specialized topics that only statisticians...

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Revisiting package dependencies

July 29, 2014
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Revisiting package dependencies

by Andrie de Vries In my previous post I wrote about how to identify and visualize package dependencies. Within hours, Duncan Murdoch (member of R-core) identified some discrepancies between my list of dependencies and the visualisation. Since then, I fixed the dispecrancies. In this blog post I attempt to clarify the issues involved in listing package dependencies. In miniCRAN...

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Data Caching

July 28, 2014
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Data caching is not new. It is often necessary to save intermediate data files when the process of loading and/or manipulating data takes a considerable amount of time. This problem is further complicated when working with dynamic data that changes regularly. In these situations it often sufficient to use data that is current with in some time frame (e.g....

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A Few Notes on UseR! 2014

July 25, 2014
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A Few Notes on UseR! 2014

It has been a month since the UseR! 2014 conference, and I'm probably the last one who writes about it. UseR! is my favorite conference because it is technical and not too big. I have completely lost interest in big and broad conferences like JSM (to me, it has become Joint Sightseeing Meetings). Karl has written two blog posts...

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Things to try after useR! – Part 1: Deep Learning with H2O

July 25, 2014
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Things to try after useR! – Part 1: Deep Learning with H2O

Annual R User Conference 2014The useR! 2014 conference was a mind-blowing experience. Hundreds of R enthusiasts and the beautiful UCLA campus, I am really glad that I had the chance to attend! The only problem is that, after a few days of non-stop R talks, I was (and still am) completely overwhelmed...

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