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Flag Robustness Issues via Offline KB Matching

Source: R/advise_offline.R
flag_robustness.Rd

Evaluates the KB decision table (category "robustness" rules) against the diagnostic signals extracted from a fitted EventStudyTask or a precomputed es_diagnostics object, and returns a severity-ranked es_advice S3 object.

Usage

flag_robustness(x, provider = NULL, ...)

# Default S3 method
flag_robustness(x, provider = NULL, ...)

# S3 method for class 'EventStudyTask'
flag_robustness(x, provider = NULL, ...)

# S3 method for class 'es_diagnostics'
flag_robustness(x, provider = NULL, ...)

Arguments

x

A fitted EventStudyTask (after fit_model()) or a precomputed es_diagnostics object returned by es_diagnostics().

provider

Accepted but ignored in the offline path — present only so the Phase 7 call shape is forward-compatible. Default NULL.

...

Additional arguments (currently ignored).

Value

An S3 object of class "es_advice" — see recommend_stat for field descriptions. Rules are filtered to category == "robustness".

Details

No LLM provider, network connection, or API key is required. The returned es_advice object has the same shape as the Phase 7 Advice contract, flagged is_deterministic = TRUE and source = "offline_kb".

See also

recommend_stat, es_diagnostics, es_kb

Examples

if (FALSE) { # \dontrun{
task <- run_event_study(my_task, ParameterSet$new())
advice <- flag_robustness(task)
print(advice)
} # }