Blog Archives

What does CNN have in common with Carmen Reinhart, Kenneth Rogoff, and Richard Tol: They all made foolish, embarrassing errors that would never have happened had they been using R Markdown

September 19, 2014
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What does CNN have in common with Carmen Reinhart, Kenneth Rogoff, and Richard Tol:  They all made foolish, embarrassing errors that would never have happened had they been using R Markdown

Rachel Cunliffe shares this delight: Had the CNN team used an integrated statistical analysis and display system such as R Markdown, nobody would’ve needed to type in the numbers by hand, and the above embarrassment never would’ve occurred. And CNN should be embarrassed about this: it’s much worse than a simple typo, as it indicates The post

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Plotting Flows with riverplot

August 14, 2014
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Plotting Flows with riverplot

I have been looking for an intuitive way to plot flows or connections between states in a process. An obvious choice is a Sankey Plot, but I could not find a satisfactory implementation in R… until I read the riverplot post by January Weiner. His riverplot package does precisely what I am need. Getting your

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Commitments of Traders: Moves in the Last Week

August 9, 2014
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Commitments of Traders: Moves in the Last Week

In my previous post I gave some background information on the Commitments of Traders report along with a selection of summary plots. One of the more interesting pieces of information that one can glean from these reports is the shift in trading sentiment from week to week. Below is a plot reflecting the relative change

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Comrades Marathon: A Race for Geriatrics?

July 22, 2014
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Comrades Marathon: A Race for Geriatrics?

It has been suggested that the average Comrades Marathon runner is gradually getting older. As an “average runner” myself, I will not deny that I am personally getting older. But, what I really mean is that the average age of all runners taking part in this great event is gradually increasing. This is not just

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Stan goes to the World Cup

July 13, 2014
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Stan goes to the World Cup

I thought it would be fun to fit a simple model in Stan to estimate the abilities of the teams in the World Cup, then I could post everything here on the blog, the whole story of the analysis from beginning to end, showing the results of spending a couple hours on a data analysis. The post

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Comment of the week

June 27, 2014
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This one, from DominikM: Really great, the simple random intercept – random slope mixed model I did yesterday now runs at least an order of magnitude faster after installing RStan 2.3 this morning. You are doing an awesome job, thanks a lot! The post Comment of the week appeared first on Statistical Modeling, Causal Inference, and...

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Twins, Tripods and Phantoms at the Comrades Marathon

June 12, 2014
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Twins, Tripods and Phantoms at the Comrades Marathon

Having picked up a viral infection days before this year’s Comrades Marathon, on 1 June I was left with time on my hands and somewhat desperate for any distraction. So I spent some time looking at my archive of Comrades data and considering some new questions. For example, what are the chances of two runners

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Concatenating a list of data frames

June 6, 2014
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It’s something that I do surprisingly often: concatenating a list of data frames into a single (possibly quite enormous) data frame. Until now my naive solution worked pretty well. However, today I needed to deal with a list of over 6 million elements. The result was hours of page thrashing before my R session finally

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Identifying pathways for managing multiple disturbances to limit plant invasions

June 5, 2014
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Andrew Tanentzap, William Lee, Adrian Monks, Kate Ladley, Peter Johnson, Geoffrey Rogers, Joy Comrie, Dean Clarke, and Ella Hayman write: We tested a multivariate hypothesis about the causal mechanisms underlying plant invasions in an ephemeral wetland in South Island, New Zealand to inform management of this biodiverse but globally imperilled habitat. . . . We The post

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Bayesian nonparametric weighted sampling inference

May 28, 2014
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Bayesian nonparametric weighted sampling inference

Yajuan Si, Natesh Pillai, and I write: It has historically been a challenge to perform Bayesian inference in a design-based survey context. The present paper develops a Bayesian model for sampling inference using inverse-probability weights. We use a hierarchical approach in which we model the distribution of the weights of the nonsampled units in the The post

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