Rmissax Full -

report_path <- write_report(imp_res,
                            diagnostics = list(mcar = mcar_res,
                                               mar = mar_res,
                                               mnar = mnar_res),
                            output_file = "RmissAX_full_report.html")

The report contains:

| Component | Description | |-----------|-------------| | CLI Parser | Uses Python’s argparse (or click) to expose a rich set of sub‑commands (scan, exploit, report). | | Task Scheduler | A lightweight asynchronous queue (based on asyncio or concurrent.futures) that distributes work across CPU cores. | | Plugin Loader | Dynamically discovers modules in the plugins/ directory, validates their manifest (plugin.yaml), and registers them with the engine. | | Result Store | In‑memory structures that are serialized to the requested output format at the end of a run. Supports incremental flushing to disk for long scans. | rmissax full

rmissax --version
# Expected output, e.g.: rmissax 2.3.1

# Load a realistic dataset (simulated)
library(survival)
data(lung)               # contains many NAs (e.g., in 'ph.ecog')
lung_clean <- lung %>% rename_all(tolower)
# Run full mode (auto method selection, 10 imputations)
lung_imp <- RmissAX::run_full(lung_clean,
                              n_imp = 10,
                              seed = 1234,
                              parallel = TRUE)
# Quick look at the pooled Cox model
library(survival)
cox_fit <- coxph(Surv(time, status) ~ age + sex + ph.ecog, data = lung_imp$imputed_data)
summary(cox_fit)

What you get: