Exception: min_trace (wls_var) needs covariance matrix to be positive definite. about hierarchicalforecast HOT 6 CLOSED

Hey @vinaybridge,

You can use MinTrace's mint_shr_ridge parameter to help with the invertibility of the covariance matrix:
https://nixtla.github.io/hierarchicalforecast/methods.html#mintrace

Another strategy to improve the covariance's invertibility is to use a bit of random noise in the series.
See the FavoritaHierarchicalDataset.load_item_data normal noise example:
https://github.com/Nixtla/hierarchicalforecast/blob/main/experiments/hierarchical_baselines/nbs/run_favorita_baselines.ipynb

from hierarchicalforecast.

Hi @kdgutier , Thank you for possible solution. I have tried MinTrace(method="mint_shrink",nonnegative=True) but it is running very slower than "OLS" , so how to speed up it ?
Any idea

from hierarchicalforecast.

MinTraceSparse might be already available if you install hierarchicalforecast from github main:

!pip install git+https://github.com/Nixtla/hierarchicalforecast.git

from hierarchicalforecast.

Not able to import it, Can you share template code for MinTraceSparse ?

from hierarchicalforecast.

Installed package from

!pip install git+https://github.com/Nixtla/hierarchicalforecast.git

from hierarchicalforecast.

I recommend you start a new conda or pip virtual environment.
Alternatively, you can try to upgrade the package

!pip install --upgrade git+https://github.com/Nixtla/hierarchicalforecast.git

from hierarchicalforecast.