Javier Escobar Ortiz

Hello @hdattada, Yes, that is a bug we found in version 0.4.3. You can read a full description in this [issue](https://github.com/JoaquinAmatRodrigo/skforecast/issues/151). We fixed it in version 0.5.0. We are still...

Hi @spike8888, The error occurs when `max_lag` > observations used for training. In your example: max_lag = 12 initial_train_size = 18 Therefore, the number of observations used in `fit` is...

Hello @spike8888, Could you show an example of your grid_search? I didn't understand your problem. Regarding `max_lag`, the training matrix will have a length equal to `len(y) - max_lag`. So,...

Hello @spike8888, You can find a good explanation about lags and the training matrix in the [documentation](https://joaquinamatrodrigo.github.io/skforecast/latest/quick-start/introduction-forecasting.html) or even googling it. To summarize, in an autoregressive model the model is...

Hello @CalenDario13! Nowadays Bayesian Search is not available in skforecast. Our intention is to implement it soon in the 0.5 version. Thank you for your comments!

Hi @spike8888, @CalenDario13, Here is an example of using Optuna with Skforecast 0.4.3. For the search, I use `backtesting_forecaster` as validation (the same validation that is used in `grid_search_forecaster`) ```python...

Hello @spike8888, With this info, the only error that I see is that you didn't pass the argument `lags_grid` to `grid_search_forecaster`. If I didn't misunderstand your code, this should work:...

Hello @kaionwong, Without seeing the code it is a bit complicated to imagine the problem and answer the questions. The spikes can be caused by seasonality factors in the past...

Hello @nkotwal93, Thanks for the note. Correct, `last_window`'s length should be the same as the **maximum lag**. In this case, the correct would be _"if the forecaster uses lags 1,...

Hello @zora-no, > 1. If I create this df, where/ how can I pass it (since it would still be separate from the "normal" Xtrain matrix)? To add exogenous variable...