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When running many time series we want to experiment. Using global models and nested models is a natural thing to do when there are not too many time series.
It would be nice to have a simple way to t…
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### Describe the feature you want to add to this project
Hi,
There are already good tutorials for time series forecasting, but they mainly focus on statistical model.
Is it possible to create one…
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First of all, I would like to thank the author of this useful integration of GluonTs in R.
My issue concerns the Python Environment setup. As per the thread title: `reticulate::py_module_available(…
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@mdancho84
Hi There,
Thank you for your amazing work in developing the package. In terms of the time series forcasting algorithm, is it possible to inlclude the long short-term memory (LSTM) ne…
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Hi Matt,
Requesting for you to add k-fold and ts-fold feature to your nested forecasting. I am starting to use the nested forecasting a lot but I get poor results if the recent couple months (my t…
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There are really two interrelated points here worth considering adding to the modeltime ecosystem that I think will be potentially valuable contributions to an already excellent package. Importantly, …
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```
library(modeltime)
library(timetk)
library(tidyquant)
library(tidyverse)
library(tidymodels)
horizon %
mutate(
rsi = TTR::RSI(outcome) # using e.g. mean() from bas…
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Haewon and I noticed that model future years were defined twice in the old data system -- in A_common_data.R called X_future_years and in A_modeltime_data.R called X_model_future_years. This creates i…
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This is a great package for automated large scale forecasts!
Currently (0.1.0), there are lot of imports. On some systems, it takes a long time and dependency packages will not get installed.
Its …