ALDEx3 1.2.0

New Features

Added method = "blmm": an ALDEx3-specific approximate mixed-effects engine using a batched profiled REML anchor fit per feature, draw-specific local covariance updates, and exact conditional GLS fixed-effect solves. Falls back to lme4 for features where the approximation cannot be evaluated cleanly.
On small datasets (with S) blmm is approximately 40x faster than lme4, that factor should increase substantially as S increases to more realistic levels.
Added feature-level parallelism (n.cores) for method = "blmm" and method = "lme4".
Added dedicated mixed-effects vignette covering model setup, BLMM formulation, validation guidance, and runtime comparison with exact lme4.

Added aldex.plot() for pairwise ALDEx3 model contrasts, with volcano, effect, MA, and waterfall plot modes.
Added aldex.effect() for ALDEx2-inspired effect diagnostics on a single binary ALDEx3 contrast. The function reports the mean contrast estimate, mean pooled within-group standard deviation, mean Cohen’s d, and an ALDEx2-style directional overlap diagnostic.
Updated cohensd() documentation and preserved its legacy return value: a feature by Monte Carlo sample matrix of Cohen’s d draws.
Effect diagnostics and MA plots now use reconstructed log abundance, logComp + logScale, and clearly report that they require stored Monte Carlo arrays.
Fixed the Quickstart vignette setup so package data such as gut_crohns_data is available during vignette rebuilds.

1000x (approx) speed up in HC3 and HC0 standard error calculations. Note this was rate limiting before so this is a huge performance boost.
Fixed error with how the streamsize variable was calibrated. Leads to massive improvement in memory management.

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