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I came across the need to implement forecasting methods at my work place. After doing some research, I realized that we even have this functionality in [excel](http://www.real-statistics.com/time-seri…
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Referencing: https://github.com/tensorflow/probability/issues/343#issuecomment-480952321
Trying to clarify my understanding of best practices for forecasting with STS. So I'm good up until:
```
q…
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Hi,
Couple of things I don't get:
I made an input csv data as described, along the lines of:
```
y,y1,y2,y3
1 2 3 32 4 56 66,37,18,23
```
Just with much more data for y (the time-series whi…
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In this session i will introduce audience to the concept of forecasting and live code demo for forecasting and showcase time series example that have strong seasonal effects and several seasons of his…
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## Describe the Problem ##
Merging pull request dtcenter/MET#2963 for the forecast climo config options of issue dtcenter/MET#2924 triggered this [METplus Testing Workflow](https://github.com/dtcente…
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### Model description
**TimesFM** (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.
### Open source status
- [X] …
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**Submitting author:** @thierrymoudiki (Thierry Moudiki)
**Repository:** https://github.com/Techtonique/ahead
**Branch with paper.md** (empty if default branch): paper
**Version:** v0.11.0
**Editor:**…
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### Description
Based on the paper: https://arxiv.org/pdf/2402.19072
### Use case
Empowering Transformers for Time Series Forecasting with Exogenous Variables
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Issue collecting design discussion related to the boundary between `sktime` and `pytorch-forecasting`, with a particular focus on foundation models and weight management, also see `sktime` issue https…
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**Problem description**
In certain cases for time series forecasting you would like to have as much data as possible for training, however, if you account for too much training data in certain models…