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laplace_sample: expose CmdStan's diagnostic_file (the Hessian at the mode)

Aperta
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#868 1 commento 0 reazioni 0 assegnatari Vedi su GitHub

@atarutin ci sta già lavorando.

Dal 9/10/2026.

  • #870 di @atarutin — aperta

Valutazione

Difficoltà
3/5
Tempo stimato
1-2 giorni
Idoneità per principianti
25/100
Tipo di issue
Funzionalità
Chiarezza
Abbastanza chiara
Stato di attività
Ferma
Stack tecnologico
python
Ambito
backend

Direzione di ricerca

Start from CmdStanModel.laplace_sample and compare it with how sample handles save_diagnostics, since the issue proposes mirroring that argument. The result would be exposed on CmdStanLaplace as a hessian attribute. Pull request #870 is already open against this issue, so check it before starting. Done means the diagnostic file is requested, parsed, and its Hessian is available when requested.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

Summary

CmdStan's laplace method can write a diagnostic file (output diagnostic_file=...), but CmdStanModel.laplace_sample has no argument to request it. That file is where CmdStan reports the Hessian at the mode, so cmdstanpy users can't get the Hessian the Laplace approximation was built from.

Details
  • laplace_sample's signature in 1.3.0 is (data, mode, draws, *, jacobian, seed, output_dir, sig_figs, save_profile, show_console, refresh, time_fmt, timeout, opt_args). There is no diagnostic_file or save_diagnostics, unlike sample(save_diagnostics=...).
  • In CmdStan 2.40.0, running laplace mode=<mode.csv> ... output file=lap.csv diagnostic_file=lap_diag.json writes a JSON file whose "Hessian" key holds the Hessian of the log density at the mode, on the unconstrained scale. We confirmed this by running it directly.
Use case

We fit a model by optimize (MLE, jacobian=False) and want observed-information standard errors at the optimum. The Hessian at the mode is that object. Through cmdstanpy we can only get the Laplace draws, and from those we'd have to re-estimate a covariance that CmdStan has already computed exactly.

Suggested API

Add a save_diagnostics: bool = False argument, mirroring sample. It would pass diagnostic_file=<output_dir>/<name>-diagnostic.json to CmdStan, and expose the parsed file on CmdStanLaplace. For example, CmdStanLaplace.hessian would return an np.ndarray, or None if the diagnostic file wasn't requested.

We are happy to open a PR with a test, if this API is acceptable.

Versions

cmdstanpy 1.3.0, CmdStan 2.40.0, Python 3.12, Linux x86_64.

Lingua principale
Python
Stelle
198
Fork
82
Merge medio
4g 11h
PR unite (30g)
3

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