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Forecasts in the EFI NEON challenge are all explicitly site-based timeseries.
With the widespread availability of remote sensing & imagery data and the importance of understanding spatially expli…
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Except for time-series data, HydPy projects usually only consist of Python code. On one side, we have the network, control parameter, and initial condition files defining a hydrological model for a s…
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Hi andreacini! Thank you for your extraordinary work but I have some questions. As I see in 'Multivariate Time Series Forecasting with Latent Graph Inference' it has no open-source official code, so I…
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Hi,
I would love to see an example WebApp built for time series applications (mostly forecasting for stock markets). The primary features would be:
- Real time trading with any pluggable model o…
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This post isn't about a particular problem with the package, but rather how to understand the results and improve the model. I hope this is the right place to post.
I work for a company that helps …
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### Describe the workflow you want to enable
I would like to be able to compare whether one forecast is statistically better than another.
### Describe your proposed solution
Under certain conditio…
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Hi,
I have noticed that the predictions with the sts package are sometimes inconsistent over multiple runs, especially when the model is fit with a variational inference surrogate. Running the same …
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Dear, @mdancho84 @AlbertoAlmuinha
### There is the possibility of viewing the metrics in the resampling forecast by ID, I saw that summary_fns = NULL #1 #3 provides the results by resampling fold…
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Hi, I am using fbprophet on daily time series with 5 years of data. Due to this covid-19 pandemic most of our metrics are impacted. Because we are using last 20% of data for testing, so it is not able…
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This project focuses on forecasting future web traffic for 145,000 Wikipedia articles. The task involves analyzing historical data and predicting real future events. Participants can explore various m…