Initialised EWM
Currently, with an exponential weighted moving window, there are two options, adjusted, or non-adjusted. The first one results in excessively high variance at the beginning of the series, the second results in an artificially low mean. Another alternative is to intialise the series with a scalar value - most obviously the mean. Here is a comparison of how these three variations look:

![ewm_variations](https://cloud.githubusercontent.com/assets/167164/16793921/ee7ad1ae-4917-11e6-800e-5969eeab1507.png)

This is from a hacky iterative implementation I just wrote as a proof of concept, but it shouldn't be hard to write an implementation that's just as efficient as the adjusting version. If this seems useful, I'm happy to make  a PR.

What would be the best API design? Perhaps just add an `initialise=None` that accepts floats, and overrides the `adjust=` argument if it is set?
