Detect outliers by different from reference signal

[cwhanse]

1. add functions to outlier.py that label outliers in a timeseries based on deviations from a reference signal. The current functions in outlier.py find outliers using either the time series' marginal distribution (zscore, tukey) or sliding windows of the time series (hampel). I don't know how to define an outlier from the deviation of signal from reference, but perhaps the existing outlier methods apply?

2. add functions to outlier.py to identify threshold curves in a time series. The geometry is intuitive, but the statistics can seem complicated and out of reach. Maybe there's a version of quantile regression that can be applied here.

See discussion in #223.

[williamhobbs]

I put together a gist that starts to explore some ideas: https://gist.github.com/williamhobbs/5eaf7c4f134ad34ba15e9a0c6e5d4165. It's a bit messy, but I thought I'd share in case it gives anyone else some ideas...