- Updated README.md to provide a comprehensive overview of Fugue, highlighting its production-ready features and extensive capabilities.
- Added detailed sections on library features, quick start instructions, core concepts, and validation/testing methodologies.
- Introduced a new example for Bayesian linear regression, demonstrating practical usage and enhanced diagnostics.
- Improved formatting and organization of existing examples for better clarity and usability.
- Refactored code in example files to ensure consistency and adherence to best practices.

- Updated CHANGELOG.md to reflect major academic improvements, performance optimizations, and new features in version 0.3.0.
- Removed the deprecated AdaptiveScales struct from the codebase, encouraging users to transition to DiminishingAdaptation for better theoretical properties.
- Enhanced various modules with improved parameter validation and error handling for robustness.

- Updated README.md to introduce the new type-safe distribution system, highlighting its benefits and key improvements.
- Added a new section demonstrating type-safe usage of Bernoulli, Poisson, and Categorical distributions with natural return types.
- Introduced a new example file `fully_type_safe.rs` showcasing the type-safe distribution system in action.
- Refactored existing examples to utilize type-safe boolean comparisons and improved clarity in probabilistic modeling.
- Enhanced documentation across various modules to reflect changes in distribution handling and type safety.

- Updated distribution constructors (e.g., Normal, Bernoulli, Poisson) to utilize safe constructors with validation, ensuring parameters are checked for correctness.
- Refactored examples and tests to demonstrate the new type-safe distribution system, improving clarity and usability.
- Enhanced README.md to reflect changes in distribution handling and provide examples of safe usage.
- Introduced a new test suite for validating distribution constructors and their parameters, ensuring robustness against invalid inputs.
- Improved error handling in the core library to provide clearer feedback on parameter validation failures

- Updated `Cargo.toml` to include `criterion` for benchmarking and added a new `memory_benchmarks` file for performance testing of memory management optimizations.
- Enhanced `Cargo.lock` with new dependencies including `criterion`, `ciborium`, and others to support the latest features and improvements.
- Refactored `TraceBuilder` and `TracePool` in `memory.rs` to improve memory allocation efficiency and added statistics tracking for the trace pool.
- Introduced various benchmarks to evaluate the performance of memory management strategies, including trace building and pooling efficiency.

- Introduced a new benchmark suite for MCMC algorithms in `benches/mcmc_benchmarks.rs`, focusing on performance improvements and diagnostics.
- Updated `Cargo.toml` to include the new `mcmc_benchmarks` benchmark group.
- Modified the `DiminishingAdaptation` struct in `mcmc_utils.rs` to store scales and their cached logarithms, optimizing performance during adaptation updates.
- Enhanced the `get_scale` and `update` methods to utilize cached logarithmic values, reducing computational overhead.

- Updated the Metropolis-Hastings algorithm to utilize type-safe proposal strategies, ensuring that proposals respect the original types of parameters (e.g., bool, u64, usize).
- Introduced new proposal strategies (GaussianWalkProposal, FlipProposal, DiscreteWalkProposal, UniformCategoricalProposal) to improve proposal generation based on value types.
- Enhanced documentation to clarify the limitations of the current implementation regarding distribution-aware proposals, particularly for bounded distributions like Beta.
- Added comprehensive tests to validate the type safety of the MCMC implementation, ensuring that types are preserved across various parameter types during sampling.
- Improved the proposal function to leverage the new strategy traits, enhancing numerical stability and type safety in the proposal process.

- Updated `mcmc_benchmarks.rs` to enhance readability and maintainability by reorganizing imports and formatting code.
- Improved the performance benchmarks for DiminishingAdaptation and MCMC diagnostics, ensuring thorough testing of adaptation strategies.
- Refactored memory benchmarks in `memory_benchmarks.rs` for consistency and clarity, including adjustments to address patterns and trace pool efficiency.
- Enhanced the `mcmc_utils.rs` file by cleaning up unnecessary whitespace and ensuring consistent formatting across functions.
- Updated tests in `type_safe_mh_tests.rs` to validate type safety and proposal strategies, ensuring robust performance across various parameter types.

…testing, and benchmarking

- Added core dependencies: `rand`, `rand_distr`, and `libm`.
- Introduced CLI dependency: `clap` with derive feature.
- Included testing dependency: `proptest`.
- Added benchmarking dependency: `criterion` with HTML reports feature.

- Introduced a comprehensive documentation style guide to ensure consistency across the Fugue repository, covering module structure, common patterns, performance considerations, and maintenance guidelines.
- Added a standardized README template for modules, outlining essential sections such as overview, quick start, components, usage examples, and design principles to facilitate uniform documentation practices.
- Enhanced existing README files in core, inference, and runtime modules with improved structure and clarity, aligning with the new style guide.

- Introduced a comprehensive error handling framework in the `error.rs` module, featuring structured error types with rich context information for better debugging.
- Added `ErrorCode` and `ErrorCategory` enums for programmatic error categorization and handling.
- Enhanced `FugueError` to include error codes and context, improving the clarity of error messages.
- Implemented helper methods and macros for convenient error creation and context management.
- Updated distribution constructors and validation methods to utilize the new error handling system, ensuring consistent error reporting across the library.
- Added extensive tests to validate the new error handling features, including error codes, context information, and helper macros.

- Introduced a Makefile to streamline development tasks, including targets for testing, coverage reports, linting, and code formatting.
- Added commands for generating coverage reports using cargo-tarpaulin and cleaning build artifacts.
- Updated .gitignore to exclude coverage reports and profiling files, ensuring a cleaner repository.
- Enhanced README with CI badge and Codecov integration for better visibility of test coverage and continuous integration status.