Monthly Archives: March 2015

Interesting Q/A: autocorrelation for categorical var in MCMC

From http://stats.stackexchange.com/questions/10798/measures-of-autocorrelation-in-categorical-values-of-a-markov-chain, a question I run into from time to time:
> Are there any measures of auto-correlation for a sequence of observations of an (unordered) categorical variable?

An (accepted) answer that got me thinking:
> [L]ook directly at the convergence rate for the Markov chain.

My interpretation, in PyMC2 terms: run chain, calculate empirical transition probabilities for categorical variable, examine spectral gap.

Experimental notebook tk.

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Interesting Q/A: some good questions about data transformation

I’m continuing my class-prep practice of searching through Cross-Validated questions with tags corresponding to upcoming class topics, and here are some interesting ones I found about data transformations:

http://stats.stackexchange.com/questions/46418/why-is-the-square-root-transformation-recommended-for-count-data
http://stats.stackexchange.com/questions/1444/how-should-i-transform-non-negative-data-including-zeros
http://stats.stackexchange.com/questions/27951/when-are-log-scales-appropriate
http://stats.stackexchange.com/questions/90149/pitfalls-to-avoid-when-transforming-data
http://stats.stackexchange.com/questions/60777/what-are-the-assumptions-of-negative-binomial-regression

The last one isn’t really about data transformations, but is still interesting.

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