July 2014 Archives

Invasion of the jellyfish!

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It seems like I'm the only one along the coast of Maine not to have seen a jellyfish this year.  That's probably more a comment on my lack of contact with the ocean because, by all reports, there are tons of jellyfish along the coast of Maine this year.

Everyone on the coast is talking about jellies, and it seems that Nick and I are what pass for jellyfish experts.  Perhaps someday we'll get a massive Calanus outbreak, but until then, it's really fun to have people talking about the ocean.  Although we don't know a whole lot of what a normal jellyfish year looks like, it's pretty clear that this year is unusual.  I think it's noteworthy that this summer is warm and that the reports started coming in when we had a big jump in temperature in early June.  The other year with lots of jellyfish chatter was 2012.  Still, lots of work is needed to really put this story together.

If you need your Nick and Andy fix, check us out in the Portland Press Herland and on the radio at MPBN.  Until I get to the ocean to get some real underwater jellyfish pics, here's one of me dressed as a jellyfish:

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photo by Petri Touhimaa, GMRI

Crash course in ABC

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On July 3rd and 4th, the Australian Statistical Conference put on a free satellite workshop at the University of New South Wales, which introduced Approximate Bayesian Computation (ABC) to anyone interested. Having some familiarity with Bayesian statistics and a strong curiosity for ABC, I decided it was worth my 4th of July to attend. 

The first day of the workshop provided a crash course in ABC methods, while the second day consisted of lectures on ABC applications to research. It turns out that approximate Bayesian analysis is useful when the likelihood function is computationally intractable and when likelihood-based inference models are unavailable. ABC is a non-parametric Bayesian method where pseudo data is generated by a candidate \theta parameter. The summary statistics from the two data sets are compared and if they are similar, then \theta is acceptable for the real data. We use this procedure to estimate the posterior distribution of the parameters of a model. This gets more complicated with dimensionality, but I'll leave that to the Bayesian experts for now. Wikipedia has a decent explanation on this for those who are interested. 

ABC is a fairly new statistical frontier that dates back to only the 1980s. It started as a niche idea in population genetics and is now gaining momentum in mainstream statistics. Although ABC still feels a bit weird and awkward to me, my gut intuition is that these methods will become useful when modeling other natural systems too. 

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This page is an archive of entries from July 2014 listed from newest to oldest.

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