winn 0.1.5

• Marked the optional ComBat example as a longer-running example because loading its Bioconductor dependency can exceed five seconds on CRAN. It remains runnable with example() and is checked by --as-cran.
• Added routine ComBat integration coverage for preserved matrix labels, finite non-negative output, and correction of simulated batch effects.
• Simplified the description and clarified the title as mass spectrometry profiling data. The full method citation remains in CITATION and the README.

winn 0.1.4

• Made the Bioconductor package sva optional for the ComBat correction path; the default ANOVA workflow no longer requires a Bioconductor installation.
• Added executable examples for all exported functions and seeded stochastic examples for reproducible CRAN checks.
• Made drift testing and smoothing honor run_order independently of matrix column order. Values are sorted within batch for testing and correction and restored to the caller’s original column order.
• Changed the Ljung-Box default to fitdf = 0, because WiNN does not first fit an ARMA model. The legacy fitdf = 1 behavior remains available explicitly through ljung_box_fitdf = 1.
• Added strict validation for finite, non-negative log-scale inputs; complete batch and run-order metadata; unique within-batch run orders; control indices; dilution factors; and within-batch scaling.
• Documented the preprocessing policy for zero and censored observations. Numeric zeros remain observed values and are never silently converted to missing values.
• Added return_details = TRUE to winn() for machine-readable selected parameters, batch assignments, and per-stage decisions while retaining the corrected-matrix default.
• Clarified fixed versus auto-mode settings and the selective ANOVA versus global ComBat correction scopes.
• Removed interactive test code from package sources and added release CI.

winn 0.1.3

• Replaced the legacy upper-priority MAD branch with independent two-tail shrinkage. Each metabolite’s median, MAD, thresholds, and upper/lower masks are computed once from the original finite values; both tails are then adjusted in one non-iterative pass.
• Added regression coverage for simultaneous-tail adjustment, one-pass threshold reuse, missing/non-finite values, and zero-MAD features.

winn 0.1.2

• Added winn_ablation() for fixed-parameter cumulative and gate-factorial analyses using the same correction operators as winn().
• Added optional decision and correction diagnostics to the drift, batch, and dilution-normalization functions. Their default matrix-returning behavior is unchanged.
• Made selective, forced-all, and disabled drift and batch gates explicit for controlled method evaluation.
• Documented the historical directional MAD behavior and added regression tests that made the legacy branch explicit before its replacement in 0.1.3.
• Added tests for ablation equivalence, disabled-stage pass-through behavior, diagnostic structure, and standard-smoother fallback reporting.