Monthly Archives: August 2013

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

August 31, 2013
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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 post Win Your Fantasy Football Snake Draft with this Shiny App in R appeared first on Fantasy Football Analytics.

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

August 31, 2013
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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...

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StarCluster and R

August 31, 2013
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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 documentationStarCluster provides a convenient way to quickly set up a cluster of machines to run some data parallel jobs using a distributed memory framework.Install...

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Introducing ‘propagate’

August 31, 2013
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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

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GitHub Package Ideas I Stole

August 31, 2013
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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 →

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MLB Rankings Using the Bradley-Terry Model

August 31, 2013
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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...

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

August 31, 2013
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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...

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Visualising Shrinkage

August 31, 2013
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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...

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Encouraging citation of software – introducing CITATION files

August 30, 2013
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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

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The joy and martyrdom of trying to be a Bayesian

August 30, 2013
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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 →

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