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summary for standalone GQ, VI, etc.

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#667 10 comments 0 reactions 0 assignees View on GitHub

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Assessment

Difficulty
5/5
Estimated time
Over a week
Newbie friendliness
35/100
Issue type
Feature
Clarity
Mostly clear
Activity status
Stale
Tech stack
python

Research direction

Start by inspecting the existing CmdStanMCMC.summary() method and the high-level summary helper, then compare the outputs exposed by CmdStanMCMC, CmdStanGQ, and CmdStanVB. Determine how draws are extracted and whether Laplace approximation is supported; done means the supported sampling results have a consistent summary path and the Laplace behavior is explicitly resolved.

Written by the indexing model from the issue text.

Description

feature
Summary

Any object returned by sampling should allow .summary() to be called on it to report mean, sd, MCMC SE, quantiles, and R-hat. This includes objects returned by

  • CmdStanMCMC: MCMC sampling
  • CmndStanGQ: generated quantities
  • CmdStanVB: variational inference
  • ???: Laplace approximation

Is Laplace approximation not supported yet in CmdStanPy? It will also return a sample of multiple draws and should also include a .summary() method.

Description

One way to do this would be to have each of these wrapper objects allow the actual draws to be extracted. Right now, there is a high-level "helper" function, where if mcmc_fit is a CmdStanMCMC object, I just call mcmc_fit.summary() directly. I would rather have this work by mcmc_fit.draws() pulling out a simple draws object on which the summary() operates. Then the other object would also support a .draws() extraction and then summary() would be a standalone function that applies to a draws object rather than to the whole output of a run (I don't know what else is in the CmdStanMCMC object---I only ever use the draws).

Current Version

1.1.0

Dominant language
Python
Stars
198
Forks
81
PR merge metrics
No merged PRs in 30d

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