flag_robustness: Flag Robustness Issues via Offline KB Matching

In EventStudy: Event Study Analysis

Flag Robustness Issues via Offline KB Matching

Description

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).

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".

Value

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

See Also

recommend_stat, es_diagnostics, es_kb

Other eventstudy-advisor: AnthropicProvider, CustomProvider, OpenAICompatProvider, ProviderBase, es_advise(), es_diagnostics(), es_kb(), provider(), recommend_stat()

Examples

data(dieselgate)
task <- EventStudyTask$new(dieselgate$firm, dieselgate$index, dieselgate$request)
task <- run_event_study(task, ParameterSet$new())
advice <- flag_robustness(task)
print(advice)

EventStudy documentation built on Oct. 31, 2026, 1:07 a.m.