Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Lag-weighted Lasso in BigVar.fit #43

Open
dk1453 opened this issue Oct 28, 2022 · 0 comments
Open

Lag-weighted Lasso in BigVar.fit #43

dk1453 opened this issue Oct 28, 2022 · 0 comments

Comments

@dk1453
Copy link

dk1453 commented Oct 28, 2022

Hi and thanks for this wonderful package, it certainly helps me with my research.

My topic involves dimension reduction in VAR model. So I found this package recently and tried to explore.
While I am experimenting with different structures built in the BigVAR.fit(), I found out that it only returns one coefficient matrix from structures like 'Basic' or 'SCAD'. But When I set the structure to 'Tapered'. It returns ten matrices and I am not sure which one is the coefficient matrix. Attached is a section copied from my console.

> b <- BigVAR.fit(epu,p=1,'Tapered',1e-2)
> dim(b)
[1] 24 25 10
> b <- BigVAR.fit(epu,p=1,'BasicEN',1e-2)
> dim(b)
[1] 24 25  1
> b <- BigVAR.fit(epu,p=1,'SCAD',1e-2)
> dim(b)
[1] 24 25  1

I read the tutorial but didn't find the answer. Does anybody know why 'Tapered' gives a such result? Thanks in advance.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant