lnccbrown / lnccbrown/HSSM

Parameter processing for RLSSM models

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Dominant language
Python
Stars
124
Forks
24
Avg merge
19h 32m
Merged PRs (30d)
60

Description

**Current Implementation**
- I don't think there is a need to change the `from_user_specs()` function.
- But p_outlier handling might need a light wrapper around the likelihood function.

Contributor guide

Open the contributing guide

Research direction

Start by tracing parameter processing for RLSSM models and reviewing from_user_specs(), then inspect the likelihood function where p_outlier is handled. The issue suggests a light wrapper may be needed, but it does not name files, tests, or a concrete completion criterion; clarify the intended behavior before making changes.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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