normalblockr v0.2.0

New features

• Zero-inflation extension (ZINormalBlockVarKnownClusters/ZINormalBlockVarUnknownClusters) for data with an excess of exact zeros.
• Sparsity path on the cluster-level precision matrix (graphical lasso), with warm-starting across penalties (NormalBlockVarCollectionSparsity, sparsity = TRUE in normal_block()).
• Accelerated variational EM (SQUAREM-style extrapolation) for both known- and unknown-clustering models.
• Several clustering-initialization heuristics (ward2, kmeans, spectral, sbm, selectable via NB_control(clustering_init = )), and best_of_inits() to try several and keep the best-ELBO fit.
• refine() on NormalBlockVarCollectionClusters: post-hoc split/merge search seeded from neighboring cluster counts, to escape mediocre local optima left by independent per-q cold starts.
• New real datasets: brca_rppa (breast cancer proteomics), onema (French stream fish biomass, zero-inflated), university (WebKB text data), each with a dedicated vignette.

Other changes

• Renamed the model classes (NormalBlock* to NormalBlockVar*) for consistency; NormalBlockData is unchanged.
• NormalBlockData rescales columns of Y by default; fitted values and regression coefficients are reported back on the original scale.
• Removed the ClustOfVar dependency (the kmeansvar clustering heuristic was dropped after benchmarking showed it was both the worst-ranked and least reliable of the available heuristics).
• Package cleanup for CRAN submission: license, documentation, and package structure.