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BBNI 0.2.2

• Fixed time-series effective sample size calculation and user-defined prop.ratio behavior
• Implemented posterior thinning in run_bbni() to align with original paper methodology and added trace display thinning in plot_trace()
• Removed bitops package dependency in favor of base R bitwise functions
• Improved performance via vectorization in check_ances_matrix() and ProposalConstruction()
• Fixed node/label scaling issues in plot_bbni() for custom gene names
• Expanded vignette with reproducible yeast analysis and clarified model assumptions

BBNI 0.2.1

• Major performance optimization: ~14x speedup via vectorization in Error_LLH and implementing repeated Boolean matrix squaring in update_ancestor_matrix, keeping strict numerical equivalence with v0.1.1
• Vignette expanded and successfully compiled to demonstrate new independent (non-timeseries) mode and visualization features
• Real-world yeast dataset application realized in the vignette
• Minor code reformatting for readability

BBNI 0.2.0

• Added new visualization functions: plot_bbni(), plot_trace(), and plot_network()
• Enhanced plot_bbni() to compare inferred networks against true networks and fixed a reversed edge direction bug
• Implemented independent (non-timeseries) mode across core algorithm and data generation functions
• Upgraded run_bbni() with a progress bar, MCMC summary, burn-in parameters, and posterior edge probabilities
• Optimized MCMC mixing with logic fixes to ProposalConstruction
• Added default parameters for key user-facing functions
• Significantly expanded documentation and examples across all primary functions
• Included public yeast dataset from original paper for user testing and for vignette

BBNI 0.1.1

• Rewrote documentation, vignette, and README for clarity
• Reformatted code for readability
• Removed unused/dead code/comments
• Fixed spelling and minor typos

BBNI 0.1.0

• Initial development version.
• Refactored legacy Bayesian Boolean Network Inference code into a modular, documented R package.
• Added run_bbni() as the primary user-facing function.
• Added a vignette demonstrating network recovery from simulated data.
• Added unit tests for core network-validity and likelihood functions.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.