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

Prenormalize vector parameter to use same strategy as cosmosis #68

Closed
fjaviersanchez opened this issue Oct 30, 2024 · 3 comments
Closed
Assignees
Labels
enhancement New feature or request

Comments

@fjaviersanchez
Copy link
Collaborator

Cosmosis pre-normalizes the input parameters before taking the numerical derivatives, so the step size depends on the parameter. Add an option to do something similar, which will allow for easier validations.

@fjaviersanchez fjaviersanchez added the enhancement New feature or request label Oct 30, 2024
@fjaviersanchez fjaviersanchez self-assigned this Oct 30, 2024
@fjaviersanchez
Copy link
Collaborator Author

Preliminary implementation in #69

@fjaviersanchez
Copy link
Collaborator Author

On top of this, there's some information in this paper: https://arxiv.org/pdf/1606.03451. The idea is to select a step in each parameter that allows to see a change in the likelihood larger than 0.1 (so the differentiation is stable), and in fact, they iterate so the step in each parameter is such that the change in the chi-square is ~1.

fjaviersanchez added a commit that referenced this issue Nov 1, 2024
@fjaviersanchez
Copy link
Collaborator Author

Closed by #69

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

No branches or pull requests

1 participant