When I was a postdoc I asked a statistician a few questions and he gave me an overview of his subject. (My area was PDEs; I knew nothing about statistics.) I remember two things that he said.

- A big part of being a statistician is knowing what to do when your assumptions aren’t met, because they’re never exactly met.
- A lot of statisticians think time series analysis is voodoo, and he was inclined to agree with them.

Hi John: The time series analysis statement I think is true ( not that I do but that the statisticians view it as voodoo ) but I’m not sure why ? After Box-Jenkins, I think the econometricians have done a lot of the good work in time series analysis so maybe the statisticians don’t know about it. That’s the only thing I can come up with as to why that statement tends to be true. There a huge number of really top “statisticians” labelled as econometricians who don’t view it as voodoo. engle, phillips, zellner, granger, sargent, hendry, pesaran, perron and stock are just a few of them.

Mark

Whenever I think about time series analysis, I think of this Santa Fe Institute time series competition http://www-psych.stanford.edu/~andreas/Time-Series/SantaFe.html. Several time series were given, some with no description of what they were, and the goal was to predict tail values. The description for the last one was, “This is a vector data set, consisting of measurements of four interacting degrees of freedom of the system. The data format consists of lines spaced by equal time steps, with one column per degree of freedom. For a very interesting reason, the continuation of this data set can not be measured. Therefore, any insight into the long-term predictability that allows the set to be continued will be of interest to a very large community. The identity of this set will be announced at the Workshop.” The time series ended up being an unfinished Bach Fugue.