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Changelog

Source: NEWS.md

rfastlowess 5.0.0

Added

  • Added prebuilt GPU library release jobs and installer selection for Linux ARM64, musl/Alpine x86_64 and ARM64, and Windows ARM64.
  • Enabled the optional wgpu DirectX 12 backend for GPU-enabled Windows builds. DXC is loaded dynamically with an FXC fallback, avoiding eager imports of dxcompiler.dll and dxil.dll.
  • Added GLES for Android GPU builds with a target-scoped wgpu feature; Windows continues to omit the GLES-only loader imports.
  • Added cv_opts() to configure grouped cross-validation options for Lowess(cv = ...).
  • Added intervals_opts() and an intervals argument to Lowess(), StreamingLowess(), OnlineLowess(), and predict(), including bootstrap intervals via bootstrap.
  • Added a seed argument to Lowess(), StreamingLowess(), OnlineLowess(), and predict() for reproducible cross-validation and bootstrap resampling.
  • Added an “Alternative Software” vignette comparing rfastlowess with stats::lowess().

Changed

  • Clarified that Batch residual_sd is 1.4826 * MAD, while Streaming reports the cumulative sample standard deviation of emitted residuals.
  • Breaking change: replaced individual return_* arguments with grouped outputs, and replaced Lowess()’s four cv_* arguments with cv = cv_opts(...).
  • Breaking change: replaced confidence_intervals/prediction_intervals (and predict()’s confidence_level/prediction_level) with intervals = intervals_opts(confidence, prediction, bootstrap), and moved the cross-validation seed from cv_opts(seed = ...) to a shared seed argument.
  • Represent unavailable diagnostic metrics as R NA rather than generic NaN values.

Fixed

  • Fixed CPU Gaussian standard errors for fitted and queried values to use the full unbounded kernel support.
  • Made even-sample medians and mean-absolute residual scaling overflow-resistant for large finite values, and centered Batch/Streaming R-squared accumulation to preserve one-ULP response variation at large offsets.
  • Made Batch RMSE, MAE, and R-squared reductions scale-safe for large finite values, preserved bisquare downweighting when tuned scales exceed the numeric range, and normalized custom weights before summation in local and all-tied fits.
  • Kept AIC finite when raw residual-square sums overflow, and made local/all-tied WLS invariant to common scaling of large finite case weights.
  • Reject unused constructor options, factors/multidimensional inputs, and malformed grouped options. Keep GPU sidecars mapped for live model finalizers, try older valid sidecars, verify native ABI/version and argument counts, bound candidate probes, and check download SHA-256 digests before execution.
  • Validate Streaming/Online iterations and plain-list CV fold counts before coercion, and accept integer custom weights.
  • Detect R’s linked libc, confirm local GPU installs before probing candidates, use canonical library filenames, and activate versioned Windows GPU sidecars on restart without replacing loaded DLLs.
  • Fixed global OLS fits treating predictor values with a large offset as degenerate; translated inputs now retain their fitted slope.
  • Fixed fraction-1 global fits ignoring custom weights, including when Batch sorts observations by x.
  • Fixed Batch missing = "drop" accepting custom weights with a length different from the original input; weights are validated before rows are dropped.
  • Fixed standard errors for global weighted fits to account for observation weights and weighted prediction leverage.
  • Fixed local Batch and retained-model prediction standard errors ignoring custom_weights; local SE moments now include the per-observation case weights.
  • Fixed global fits with all-zero custom weights to honor the configured zero-weight fallback policy.
  • Fixed fraction-1 global fits ignoring configured robustness iterations; they now reweight observations and report iterations used.
  • Fixed Batch cross-validation candidate fits ignoring custom_weights; K-fold CV now rejects more folds than observations instead of returning zero scores.
  • Fixed Streaming and Online accepting invalid auto_converge tolerances; Online also rejects invalid explicit delta values while retaining NaN as its default sentinel.
  • Fixed GPU Batch fits misaligning fitted values with unsorted inputs; results now preserve input and requested sorted order.
  • Fixed GPU Batch silently ignoring custom_weights; GPU fit and CV candidate kernels now apply them directly.
  • Reduced GPU adapter buffer requirements from 30 storage/32 total buffer bindings to 7 storage/8 total per shader stage by using per-compute-pipeline resource layouts.
  • Fixed Online incremental mode accepting positive delta and auto_converge settings it cannot use; unsupported combinations now error.
  • Fixed grouped intervals discarding distinct confidence and prediction levels; each requested coverage is now applied independently.
  • Fixed the default boundary_policy ("extend") letting synthetic boundary points bias the shared robustness scale estimate used to reweight every point, compounding across robustness iterations.
  • Improved agreement with R/Cleveland on sparse, asymmetric, and high-iteration fits by aligning robustness stopping, local-linear degeneracy handling, neighborhood traversal, delta interpolation, and weighted accumulation.
  • Fixed zero-radius neighborhoods dropping tied observations or accumulating normalized weights in a different order under robust fits.
  • Fixed Gaussian fits clipping the unbounded kernel to the neighbor window and flooring far-tail weights; all observations now contribute under the standard Gaussian formula.
  • Reject fractional integer/count options and validate GPU candidate libraries and supported prebuilt targets; refuse in-place overwrite when atomic replacement fails.

rfastlowess 4.1.0

Added

Fixed

  • Changed the OnlineLowess() default iterations from 3 to 0, matching non-robust incremental updates; robustness iterations require update_mode = "full".

rfastlowess 4.0.0

Added

Changed

  • Breaking change: removed return_diagnostics, return_residuals, and parallel from the OnlineLowess() constructor; these options had no effect in online mode.
  • Breaking change: removed confidence_intervals and prediction_intervals from OnlineLowess() and StreamingLowess() constructors because those options were not computed.
  • Breaking change: the streaming overlap default now resolves dynamically to chunk_size / 10, clamped to [1, chunk_size - 10], instead of a fixed 500.
  • Improved the R API documentation, including the overlap default.

Fixed

  • Fixed the real-time vignette example failing with two data points by aligning its minimum point count with the library’s minimum of two.
  • Fixed install_gpu() replacing a loaded shared library in place; it now installs through a temporary file and atomic rename.

rfastlowess 3.2.1

Changed

  • Clarified that results are returned in input order, even though the algorithm sorts internally.

rfastlowess 3.2.0

Changed

  • Expanded and reorganized the R documentation with parameter guidance, examples, and clearer adapter-selection advice.

Fixed

  • Corrected the OnlineLowess() defaults to min_points = 2L and update_mode = "incremental".
  • Corrected the Handling Outliers example to use a fraction that downweights the injected outlier.
  • Improved the Online, streaming, merge, robustness, and use-case examples so they show representative output and run successfully.

rfastlowess 3.1.0

Changed

  • Moved R documentation to GitHub Pages using pkgdown and updated the README with package-specific guidance.
  • Lowered the minimum supported R version to 4.4.0.

Fixed

  • Fixed extra positional arguments being accepted outside the initial positional argument; constructors now reject unnamed arguments in later positions.

rfastlowess 3.0.0

Added

  • Added an opt-in GPU backend through the gpu Cargo feature and install_gpu() to download a prebuilt GPU library; using it requires restarting R.
  • Added S3 generics fit(), process_chunk(), finalize(), and add_point(), replacing the previous list-closure API.
  • Added cross-reference links in the API documentation to the corresponding user guides.

Changed

  • Breaking change: renamed the smoothed and std_error fields returned by OnlineLowess()$add_point() to y and standard_error.
  • Breaking change: added ... to Lowess(), StreamingLowess(), and OnlineLowess() so optional arguments must be named.
  • Set the minimum supported R version to 4.6.
  • Organized Streaming and Online API documentation and tutorials into dedicated user-guide pages.

rfastlowess 2.0.0

Added

  • Added custom_weights to batch fitting for non-negative per-observation weights.

Changed

  • Breaking change: replaced vector-based OnlineLowess()$add_points(x, y) with scalar add_point(x, y), which processes one point at a time and returns NULL until enough points are available.

rfastlowess 1.3.0

Fixed

  • Registered the extendr panic hook so Rust panics are reported as R errors instead of crashing the R session.

rfastlowess 1.2.0

Added

rfastlowess 1.1.2

  • Under-the-hood maintenance; no changes to the public API or runtime behavior.

rfastlowess 1.1.1

Fixed

  • Fixed GPU configuration and initialization problems, and improved recovery after missing hardware/drivers or earlier GPU execution errors.

rfastlowess 1.1.0

Added

  • Expanded GPU fitting support to selectable kernels, robustness and scaling methods, boundary policies, automatic convergence, prediction, and cross-validation.

Fixed

  • Fixed the Extend boundary policy not being applied and improved numerical precision through coordinate centering.
  • Fixed GPU integer overflow, initialization failures, and resource exhaustion.

rfastlowess 1.0.0

Added

  • Added the mean scaling method (Mean Absolute Deviation).
  • Added print() and plot() methods for LowessResult objects.

Changed

  • Breaking change: returned LowessResult S3 objects instead of raw vectors.

rfastlowess 0.99.9

Added

  • Made the package available on conda-forge as r-rfastlowess.

Changed

  • Introduced class-based builders for streaming and online processing.

rfastlowess 0.99.8

  • Under-the-hood maintenance; no changes to the public API or runtime behavior.

rfastlowess 0.99.7

Fixed

  • Fixed links in the shared project README.

rfastlowess 0.99.6

Fixed

  • Fixed formatting and links in the shared project README.

rfastlowess 0.99.5

Changed

  • Reduced the published package size by excluding development-only files.

rfastlowess 0.99.2

Added

  • Added a pkgdown documentation site and examples for exported functions.
  • Added input validation for exported functions.

Changed

  • Breaking change: renamed exported functions to avoid conflicts with base R.

Fixed

  • Fixed package startup messages.

rfastlowess 0.99.1

Changed

  • Prepared the R package for Bioconductor submission.

rfastlowess 0.99.0

Added

  • Added NoBoundary boundary handling and MAD/MAR scaling methods from fastLowess v0.4.0.

Changed

  • Changed the license from AGPL-3.0-or-later to dual MIT OR Apache-2.0.

rfastlowess 0.7.0

Added

  • Added NoBoundary handling and MAD/MAR scaling methods to the underlying LOWESS core.

Changed

  • Improved fitting and cross-validation performance through SIMD accumulation, reusable buffers, and optimized window and scale calculations.

rfastlowess 0.6.0

Added

  • Added a seed option for reproducible k-fold cross-validation.

Fixed

  • Fixed Batch and Streaming adapter conversion behavior in the LOWESS core.

rfastlowess 0.5.3

Changed

  • Improved fitting and cross-validation performance by optimizing sorting, window operations, robust scale estimation, regression, and delta interpolation.

rfastlowess 0.4.0

Added

  • Added support for fastLowess v0.4.0 fitting and cross-validation improvements.

Changed

  • Changed the license from AGPL-3.0-or-later to dual MIT OR Apache-2.0.

rfastlowess 0.3.0

Added

  • Added installation from R-universe without requiring Rust.

Changed

  • Updated the cross-validation API for fastLowess v0.3.0.

rfastlowess 0.2.0

Added

  • Added support for fastLowess v0.2.0 fitting improvements.

rfastlowess 0.1.0

Added

  • Initial R binding for fastLowess.