Monthly Archives: August 2013

Win Your Fantasy Football Snake Draft with this Shiny App in R

August 31, 2013
By

In a previous post, I showed how to determine the best starting lineup to draft in an auction draft using an optimizer tool.  In this post, I use a Shiny app in R to determine the best possible players to pick in a fantasy...

Read more »

StarCluster and R

August 31, 2013
By
StarCluster and R

StarCluster is a utility for creating and managingdistributed computing clusters hosted on Amazon's Elastic ComputeCloud (EC2). StarCluster utilizes Amazon´s EC2 web service to createand destroy clusters of Linux virtual machines on demand. Justin Riley http://star.mit.edu/cluster/docs/latest/index.html StarCluster documentation StarCluster provides a convenient way to quickly set up a cluster of machines to run some data parallel jobs using a distributed memory framework. Install...

Read more »

Introducing ‘propagate’

August 31, 2013
By
Introducing ‘propagate’

With this post, I want to introduce the new ‘propagate’ package on CRAN. It has one single purpose: propagation of uncertainties (“error propagation”). There is already one package on CRAN available for this task, named ‘metRology’ (http://cran.r-project.org/web/packages/metRology/index.html). ‘propagate’ has some additional functionality that some may find useful. The most important functions are: * propagate: A

Read more »

GitHub Package Ideas I Stole

August 31, 2013
By
GitHub Package Ideas I Stole

One of my favorite sources of good ideas is looking at the GitHub repositories of others and modeling my repos after the good ideas I see others doing. Here's Steve Jobs on stealing ideas: In the past few weeks I've … Continue reading →

Read more »

MLB Rankings Using the Bradley-Terry Model

August 31, 2013
By
MLB Rankings Using the Bradley-Terry Model

Today, I take my first shots at ranking Major League Baseball (MLB) teams. I see my efforts at prediction and ranking an ongoing process so that my models improve, the data I incorporate are more meaningful, and ultimately my predictions are largely accurate. For the first attempt, let’s rank MLB teams using the Bradley-Terry (BT) model. Before we discuss the rankings, we need...

Read more »

The Dutch Dataverse Network: a host for the ChEMBL-RDF v13.5 data, and some thoughts in workflow integration

August 31, 2013
By
The Dutch Dataverse Network: a host for the ChEMBL-RDF v13.5 data, and some thoughts in workflow integration

Last Thursday, there was a UM library network drink. And as I see a library where knowledge is found, and libraries still rarely think of knowledge as ever being able to be stored outside books and papers, I was happy to see the library promoting the D...

Read more »

Visualising Shrinkage

August 31, 2013
By
Visualising Shrinkage

A useful property of mixed effects and Bayesian hierarchical models is that lower level estimates are shrunk towards the more stable estimates further up the hierarchy. To use a time honoured example you might be modelling the effect of a new teaching method on performance at the classroom level. Classes of 30 or so students … Continue reading...

Read more »

Encouraging citation of software – introducing CITATION files

August 30, 2013
By

Summary: Put a plaintext file named CITATION in the root directory of your code, and put information in it about how to cite your software. Go on, do it now – it’ll only take two minutes! Software is very important in science – but good software takes time and effort that could be used to do

Read more »

The joy and martyrdom of trying to be a Bayesian

August 30, 2013
By

Some of my fellow scientists have it easy. They use predefined methods like linear regression and ANOVA to test simple hypotheses; they live in the innocent world of bivariate plots and lm(). Sometimes they notice that the data have odd histograms and they use glm(). The more educated ones use … Continue reading →

Read more »

Tutorial: Parallel programming with foreach

August 30, 2013
By

Exegetic Analytics extols the wonders of foreach package for iterative operations that go beyond the standard "for" loop in R. For example, here's a neat (if not optimally efficient) construct using filters to calculate the primes less than 100: foreach(n = 1:100, .combine = c) %:% when (isPrime(n)) %do% n The open-source team at Revolution Analytics created the foreach...

Read more »

Sponsors

Mango solutions



plotly webpage

dominolab webpage



Zero Inflated Models and Generalized Linear Mixed Models with R

Quantide: statistical consulting and training

datasociety

http://www.eoda.de





ODSC

ODSC

CRC R books series





Six Sigma Online Training









Contact us if you wish to help support R-bloggers, and place your banner here.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)