-
**Is your feature request related to a current problem? Please describe.**
From what I understand, seasonal decomposition is currently achieved in `darts` by calling `extract_trend_and_seasonality`…
-
The seasonality test used in auto-ARIMA relies on the non-batched implementation of the STL decomposition provided by statsmodels for the seasonality test used to find D.
A CUDA implementation would …
Nyrio updated
3 years ago
-
Hello,
I would like to know how the issue with Nan values has been handled within the code. By ignoring the missing data or simply by interpolation?
Regards,
-
The generalized ESD method normalizes deviation from the mean based on an estimate of the population variance. If the data has an uncompensated, appreciable linear trend this is equivalent to estimati…
-
Hi @brandtg,
I've been looking for a Java STL package and was psyched to find that you were working on one!
My first comparison with the Java code was for some artificial data from the NAB dataset (…
-
Hello,
first of all I would like to thank you for creating this package. I find the diagnostic plots of the stlplus package very useful. I'm writing to you because the default value of t.window seems…
-
For the API design proposal, see [this wiki entry](https://github.com/alan-turing-institute/sktime/wiki/Forecasting-API-proposal).
## Forecasters
### Atomic
- [x] NaiveForecaster (strategies={"l…
-
Need to discuss what all we want to add for version 0.3.0
-
Hi, is there any interest in implementing cross validation for estimating missing values in the package? I have a problem where I had a time steps missing at random throughout my time series, and bec…
-
When doing post-STL smoothing of the seasonal component there can be artifacts at the edge. Here is a fit for some synthetic data.
![screen shot 2017-07-14 at 5 30 46 pm](https://user-images.githu…