January 2017

Understanding mixture models and expectation-maximization (using baseball statistics)

January 2, 2017 | David Robinson

Previously in this series: Understanding the beta distribution Understanding empirical Bayes estimation Understanding credible intervals Understanding the Bayesian approach to false discovery rates Understanding Bayesian A/B testing Understanding beta binomial regression Understanding empirical Bayesian hierarchical modeling In this series on empirical Bayesian methods on baseball data, we’ve been ... [Read more...]

Django and R on Heroku

January 2, 2017 | Brian A. Fannin

I’ve been playing with Django for a while now and I’m loving it. Don’t get me wrong, I still love Shiny, but Django is pretty tough to beat for data-heavy projects and managing user sessions. For deployment, I’ve been using Heroku and am very h... [Read more...]

May the Force of R be With You, Always!

January 2, 2017 | Daniel's Blog

With my Telegram account connected to @TeleR, the force of R can always be with me, where I have data. The following is a screenshot of my mobile: If you want to have R where you are too, you will only need a Telegram account, then search for the pu... [Read more...]

eoda celebrates R – don’t miss the date and win!

January 2, 2017 | eoda GmbH

#Rstatsgoes10k: Join eoda in the celebration of R and take the chance to win with your prediction! The easiest way to stay up-to-date regarding the current number of R packages is to follow eoda’s automated Twitter bot @Rstatsgoes10k. This bot regularly informs its followers of the status ...
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Animations in R using Plotly

January 2, 2017 | Riddhiman

Like last year, lets have some fun with the Plotly package. We’ll try out Plotly’s new animation capabilities. [crayon-586941b022674144350101/] You should now have something like this: For mode details visit: Plotly for R by Carson Seivert. [Read more...]

Forcasting Natural Catastrophes (is rather difficult)

January 2, 2017 | arthur charpentier

Following my previous post, I wanted to spend more time, on the time series with “global weather-related disaster losses as a proportion of global GDP” over the time period 1990-2016 that Roger Pilke sent me last night. db=data.frame(year=1990:2016, ratio=c(.23,.27,.32,.37,.22,.26,.29,.15,.40,.28,.14,.09,.24,.18,.29,.51,.13,.17,.25,.13,.21,.29,.25,.2,.15,.12,.12)) In my previous post, I spend some ...
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What is a Linear Trend, by the way?

January 1, 2017 | arthur charpentier

I had a very stranger discussion on twitter (yes, another one), about regression curves. I think it started with a tweet based on some xkcd picture (just for fun, because it was New Year’s Day) “don’t trust linear regressions” https://t.co/exUCvyRd1G pic.twitter.com/O6...
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Dan Thompson 2017-01-29 11:29:11

January 1, 2017 | Dan Thompson

Summary In this blog post I will show you how to make your own personal assistant (think Siri, Cortana, Alexa) in R, very quickly. This will be done in three steps: Get R to recognise your voice and convert it to text Set up a system which us... [Read more...]

Building Shiny App exercises part 4

January 1, 2017 | Euthymios Kasvikis

APPLICATION LAYOUT & REACTIVITY The fourth part of our series is “separated” into two “sub-parts”. In the first one we will start building the skeleton of our application by using tabsetPanel. This is how we will separate the sections of our app and also organize its structure better. In the second ... [Read more...]
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