[ENH] sliding window (z or quantile) score based anomaly detection

Two algorithms that we could implement for starter in the sliding windo detection family:

• sliding window with parameters related to window (like in pandas). Get quantile or z score based on last window, and threshold the score.
• fit-update-predict on expanding or rolling window splitter with an arbitrary forecaster. Get forecasts, and threshold residuals. Or get proba forecasts, and compute quantile score based on those.

The first is a special case of the second, where we make a naive distributional forecast, but I think it's worth having the first separately implemented for two reasons:

• it is a common subcase, and not obvious how to obtain it as a special case of the second
• we explore implementation issues that arise from using sliding windows etc