Comments (3)
dflemin3
commented on May 27, 2024
It would be a good idea to use emcee's new fancy autocorrelation techniques, like tau = sampler.get_autocorr_time()
from approxposterior.
dflemin3
commented on May 27, 2024
Now using emcee v3's integrating autocorrelation time method as the default, but in general, user should post-process and examine their chains to confirm convergence.
from approxposterior.
dflemin3
commented on May 27, 2024
Added the ability for the user to use pretty good estimates for burn in times, or they could not do that and post-process chains. Changes are on the dev branch and will make it to master soon.
from approxposterior.
Related Issues (20)
- Optimize the GP less HOT 1
- conda installation is broke HOT 2
- Multiprocessing is slow: too much overhead spinning up new processes HOT 2
- Let users set the name of the output files HOT 1
- Scaling parameter values to improve GP hyperparameter optimization HOT 1
- Use other regression algorithms besides the GP for logprobability predictions HOT 1
- Implement Bayesian Optimization HOT 2
- Cross-Validation to select GP hyperparameters HOT 1
- Explore approxposterior parallelization paradigm HOT 1
- Utility functions for training set initialization HOT 1
- Add bounds, scale to ApproxPosterior object? HOT 1
- Can't clone from [email protected]:dflemin3 HOT 1
- Use latin hypercube sampler to initialize GP optimizations HOT 1
- Add MultiNest for posterior retreival HOT 1
- Parallel approxposterior using python 3.8+ multiprocessing
- Add a warning for when the GP optimization optGPEveryN > m HOT 1
- Standardize code formatting
- Don't use nbsphinx_prompt_width to hide prompts HOT 1
- Single parameter inference causes ValueError
- Unnecessary creation of a new GP object in `findNextPoint`
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from approxposterior.