400 search results for "shiny"

ENAR 2014 Searcher #ENAR2014

March 12, 2014
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ENAR 2014 Searcher #ENAR2014

To those going to ENAR this year: Are you trying to find who’s presenting at ENAR from your department but all that pdf searching got you down?  Are you trying to make an itinerary but dislike copying and pasting from a pdf?  Well I have a Shiny App for you! At https://muschellij2.shinyapps.io/ENAR_2014, you can see all

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Slidify my R journey from @matlabulous to rCrimemap

March 12, 2014
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Slidify my R journey from @matlabulous to rCrimemap

My LondonR Talk Thanks to Mango Solutions (LondonR organiser), I was given the opportunity last night to talk about my mini project ‘CrimeMap’. Instead of going through all the technical details behind the scenes, I chose to talk the audience through my R journey from a noob to a heavy user. CrimeMap was used as a...

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In case you missed it: February 2014 roundup

March 12, 2014
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In case you missed them, here are some articles from February of particular interest to R users: A statistical analysis of various forecasting methods (using R) leads to correct predictions for 21 of 24 Oscars awards. There are now 123 R User Groups worldwide, and applications for Revolution Analytics sponsorship grants are open until March 31. Revolution Analytics was...

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googleVis code development moved to GitHub

March 11, 2014
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googleVis code development moved to GitHub

After nearly 4 years of developing googleVis on Google Code with SVN we decided to move to GitHub. The main reason was that Google stopped the facility of hosting pre-CRAN builds of the package for user testing. The devtools package on the other hand m...

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Real-time Reporting with the Adobe Analytics API

March 10, 2014
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Starting with version 1.3.1 of RSiteCatalyst, you can now access the real-time reporting capabilities of the Adobe Analytics API through a familiar R interface. Here’s how to get started… GetRealTimeConfiguration Before using the real-time reporting capabilities of Adobe Analytics, you first need to indicate which metrics and elements you are interested in seeing in real-time. To Real-time Reporting...

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Ever wonder how popular your favorite R functions are?

March 7, 2014
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Ever wonder how popular your favorite R functions are?

How's that fried pickle sandwich treating you?  Perhaps your taste in R  functions are less bizarre than your taste in R commands?Now you can easily find out using this new shiny app!  In this post I use the R function frequency table co...

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Slidify: Modern, simple presentations written in R Markdown

February 24, 2014
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Slidify: Modern, simple presentations written in R Markdown

As a LaTeX fan I’m used to using Beamer for presentations, but the built-in themes are definitely starting to show their age — and writing a custom .sty file looks like a nightmare — so for a while I’ve been looking … Continue reading →

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Bayes factor t tests, part 2: Two-sample tests

February 23, 2014
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Bayes factor t tests, part 2: Two-sample tests

In the previous post, I introduced the logic of Bayes factors for one-sample designs by means of a simple example. In this post, I will give more detail about the models and assumptions used by the BayesFactor package, and also how to do simple analyses of two- sample designs.See the previous posts for background: What is a...

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Interactive exploration of a prior’s impact

February 21, 2014
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Interactive exploration of a prior’s impact

The probably most frequent criticism of Bayesian statistics sounds something like “It’s all subjective – with the ‘right’ prior, you can get any result you want.”. In order to approach this criticism it has been suggested to do a sensitivity analysis (or robustness analysis), that demonstrates how the choice of priors affects the conclusions drawn

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Tutorials- Statistical and Multivariate Analysis for Metabolomics

February 17, 2014
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Tutorials- Statistical and Multivariate Analysis for Metabolomics

I recently had the pleasure in participating in the 2014 WCMC Statistics for Metabolomics Short Course. The course was hosted by the NIH West Coast Metabolomics Center and focused on statistical and multivariate strategies for metabolomic data analysis. A variety of topics were covered using 8 hands on tutorials which focused on: data quality overview

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