dancing-dog

 

So I wanted to start something about Gibbs sampling with a catchy title and so I stole the APS March meeting’s dance party theme of Gettin’ Higgy with it which I take it that they stole from Will Smith’s Gettin’ Jiggy with it.  And when I googled Gettin’ Jiggy with it, I came up with a lot of pictures of dancing dogs and cats.  Thus, the picture above.  There you go.  Yes, I’m still working on my delivery.  But anyway, as I mentioned last time, Gibbs sampling is a specialized form of the Metropolis-Hastings algorithm and the idea is that we sample values from a conditional distribution than from marginal distributions.  So basically we have a bunch of variables, making up a multivariate distribution (multivariate = multi variable, get it?  Okay, so that’s not my best work, I’ll admit) and we want to get the 411 on one variable based on the info we have from other variables.  So like we have this character in my books named Tina.  In some dimensions, she’s living the high life  in big mansions, wearing flashy clothes, going all these A-list parties in Maui or LA or Manhattan and don’t you want to be her right now?  I don’t blame you.  I kinda want to be her right now too.  In some realms though, she lives a relatively quiet life working at a computer repair store or a printer shop somewhere in the Midwest or on the East Coast.  So how can we determine the probability of which world she is in and what life she is leading?  Well, there is one major factor, or should I say, another character, that allows us to determine that probability more clearly.  But I’m not saying what … or who … just yet.  But I will say that without knowing if she is with this thing or person, then, depending on the context in which she is introduced, it may be tougher to determine in which dimension she is in.  So that’s basically Gibbs sampling, sampling based on conditional probabilities.  But that’s all for now.  Tune in next time when I discuss um … uh … well, still have to think of a topic.  But I’ll try to make it good … promise!  Until then … let’s just boogie, woogie, woogie, Gibby down.  Yes, I do realize that was just awful too.  I’ll work on that as well.

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