| Element | Description | |--------|-------------| | imputed_data | The final pooled dataset (or a list of n_imp imputed tables). | | diagnostics | A tibble summarising missingness patterns, MCAR/MAR tests, and convergence stats. | | plots | A list of ggplot objects (heatmaps, missingness maps, density comparisons). | | report | An auto‑generated HTML report (saved to the working directory). |
async def probe(host: str, config: Dict) -> Dict | None: # Example: send a crafted HTTP request with a custom header import aiohttp url = f"http://host" headers = "X-My-Header": "rmissax-test" try: async with aiohttp.ClientSession() as session: async with session.get(url, headers=headers, timeout=5) as resp: if "X-My-Header" in resp.headers: return "host": host, "type": "header-reflection", "header": resp.headers["X-My-Header"], "status": resp.status rmissax full
# Run full mode (auto method selection, 10 imputations) lung_imp <- RmissAX::run_full(lung_clean, n_imp = 10, seed = 1234, parallel = TRUE) | | report | An auto‑generated HTML report
## 5️⃣ Multiple imputation ------------------------------------------------ imp <- impute_multiple(df, method_tbl = meth_tbl, n_imp = n_imp, parallel = parallel, seed = seed) config: Dict) ->