Blog Archives

Basic MCMC and Bayesian statistics in… BASIC!

August 9, 2015
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Basic MCMC and Bayesian statistics in… BASIC!

The BASIC programming language was at one point the most widely spread programming language. Many home computers in the 80s came with BASIC (like the Commodore 64 and the Apple II), and in the 90s both DOS and Windows 95 included a copy of the QBasic IDE. QBasic was also the first programming language I encountered (I used...

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Tiny Data, Approximate Bayesian Computation and the Socks of Karl Broman: The Movie

July 26, 2015
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This is a screencast of my UseR! 2015 presentation: Tiny Data, Approximate Bayesian Computation and the Socks of Karl Broman. Based on the original blog post it is a quick’n’dirty introduction to approximate Bayesian computation (and is also, in a sense, an introduction to Bayesian statistics in general). Here it is, if you have 15 minutes to...

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Easy Bayesian Bootstrap in R

July 14, 2015
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Easy Bayesian Bootstrap in R

A while back I wrote about how the classical non-parametric bootstrap can be seen as a special case of the Bayesian bootstrap. Well, one difference between the two methods is that, while it is straightforward to roll a classical bootstrap in R, there is no easy way to do a Bayesian bootstrap. This post, in an attempt to...

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Hygge at UseR! 2015, Aalborg

July 6, 2015
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Hygge at UseR! 2015, Aalborg

hygge A Danish word (pronounced HU-guh) meaning social coziness. I.e. the feeling of a good social atmosphere. – Urban Dictionary Yes, there was plenty of hygge to go around this year’s UseR! that took place last week in Aalborg, Denmark. Everybody I’ve spoken with agrees that it was an extraordinary conference, from the interesting speakers and presentations...

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Big Data and Chess Follow-up: Predictive Piece Values Over the Course of a Game

June 17, 2015
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Big Data and Chess Follow-up: Predictive Piece Values Over the Course of a Game

In a previous post I used the the Million Base 2.2 chess data base to calculate the predictive piece values of chess pieces. It worked out pretty well and here, just for fun, I thought I would check out what happens with the predictive piece values over the course of a chess game. In the previous analysis,...

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Big Data and Chess: What are the Predictive Point Values of Chess Pieces?

June 10, 2015
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Big Data and Chess: What are the Predictive Point Values of Chess Pieces?

Who doesn’t like chess? Me! Sure, I like the idea of chess – intellectual masterminds battling each other using nothing but pure thought – the problem is that I tend to loose, probably because I don’t really know how to play well, and because I never practice. I do know one thing: How much the different pieces are worth,...

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The Non-parametric Bootstrap as a Bayesian Model

April 17, 2015
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The Non-parametric Bootstrap as a Bayesian Model

The non-parametric bootstrap was my first love. I was lost in a muddy swamp of zs, ts and ps when I first saw her. Conceptually beautiful, simple to implement, easy to understand (I thought back then, at least). And when she whispered in my ear, “I make no assumptions regarding the underlying distribution”, I was in love. This love...

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A Speed Comparison Between Flexible Linear Regression Alternatives in R

March 25, 2015
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A Speed Comparison Between Flexible Linear Regression Alternatives in R

Everybody loves speed comparisons! Is R faster than Python? Is dplyr faster than data.table? Is STAN faster than JAGS? It has been said that speed comparisons are utterly meaningless, and in general I agree, especially when you are comparing apples and oranges which is what I’m going to do here. I’m going to compare a couple of alternatives to...

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Probable Points and Credible Intervals, Part 2: Decision Theory

January 7, 2015
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Probable Points and Credible Intervals, Part 2: Decision Theory

“Behind every great point estimate stands a minimized loss function.” – Me, just now This is a continuation of Probable Points and Credible Intervals, a series of posts on Bayesian point and interval estimates. In Part 1 we looked at these estimates as graphical summaries, useful when it’s difficult to plot the whole posterior in good way....

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Peter Norvig’s Spell Checker in Two Lines of Base R

December 16, 2014
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Peter Norvig’s Spell Checker in Two Lines of Base R

Peter Norvig, the director of research at Google, wrote a nice essay on How to Write a Spelling Corrector a couple of years ago. That essay explains and implements a simple but effective spelling correction function in just 21 lines of Python. Highly recommended reading! I was wondering how many lines it would take to write something similar...

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