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

Problem with attribute explanatory_space (due to method extract on MultivariateData?) #34

Open
jpeyhardi opened this issue Apr 17, 2019 · 5 comments

Comments

@jpeyhardi
Copy link
Contributor

After estimation of a GLM (Poisson, binary, nominal or ordinal), the attribute explanatory_space of the model does not works when the estimation is made from the MultivariateData. It seems to be a problem of deleted pointer.
On the contrary, there is no problem when the estimation is made from UnivariateConditionalData.
I do not understand what is different in the two approaches.

@pfernique
Copy link
Member

This issue seems to be related to StatisKit/Core#81

@pfernique
Copy link
Member

Any way, are UnivariateConditionalData and MultivariateConditionalData really useful ?
Would it be clearer to provide only one way to fit regressions using the MultivariateData along with response and explanatory indices (or names) as for the R language ?

@jpeyhardi
Copy link
Contributor Author

jpeyhardi commented May 6, 2019 via email

@pfernique
Copy link
Member

As you can see on the related issue feed, they are still some changes to do before merging the code.

PLEASE EDIT YOUR PREVIOUS COMMENT AS AN ISSUE COMMENT

@jpeyhardi
Copy link
Contributor Author

I agree with the fact that conditional data are not mandatory. It would be clearer to use only MultivariateData to fit regressions.
Did you find the problem with explanatory_space pointer ?
Thank you.

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

2 participants