Owen Vallis

Thanks for checking out the package. Line 37: We use a modification to STL which removes the median and the STL seasonal component from the original data. This is how...

@asstergi The 1s were being inserted in order to avoid plotting errors when we log transformed the y axis. However, @ahardjasa submitted a patch that now allows us to support...

Your totally right. The seasonality we were looking at was either daily (if the data was minutely or hourly), or weekly (if the data was daily). We added `AnomalyDetectionVec()` in...

Hi Elbamos, I was able to reproduce your error, and I'll look into posting a patch soon. In the interim, you can run the data using the following: `AnomalyDetectionVec(minimal[[2]], period=7,...

Hi rtjohn, We used period here to denote the number of observations in a single cycle of the dominant seasonal component. This way we can define the number of observations...

@rtjohn I see what you're saying. This [Seasonal-Trend Decomposition](http://www.wessa.net/download/stl.pdf) paper was a big part of developing the package, and we based our naming conventions around their notion of "Seasonal, Trend,...

Thanks for the suggestion. We had actually run into this, and we found that extreme anomalies can severely distort the derived trend component from STL. This meant we couldn't trust...

Thanks for the PR. Looks like there are duplicate files again for the loss and the tests, and I think you'll need to run the Black and Isort formatting (the...

Thanks for the PR! I'll review the notebook soon and I left a few comments on the loss.

@abhisharsinha, let me know your thoughts on the PR comments and we can get this merged into the dev branch.