sshist 0.2.6

Bug Fixes

• plot.sshist_2d(): the default plot title was built with a Unicode multiplication sign (U+00D7). On devices using PDF-family encodings (e.g. pdf(), which R CMD check uses for its examples and tests) this aborted with conversion failure on '...' in 'mbcsToSbcs'. The title now uses an ASCII x, so plot() works on all graphics devices. This removes the only ERROR reported by R CMD check.

Housekeeping

• inst/WORDLIST: added the package’s technical vocabulary (MVFFT, logexp, optimisation, parallelization, frontmatter, pts) and dropped stale entries (getOption, typographic-apostrophe variants of Abramson, Diaconis, Sturges, Colour). spelling::spell_check_package() now reports no typos.

Testing

• Test suite: 277 PASS | 0 FAIL | 0 ERROR | 0 WARN | 0 SKIP.

sshist 0.2.5

Bug Fixes

• ssvkernel(): replaced max(256, min(raw_points, 1000)) grid formula with min(ceil(T/dt_samp), 1000) to match the original Python/MATLAB reference. This fixes an overly fine evaluation grid (e.g. 256 → 53 points for Old Faithful waiting data) that produced a different cost landscape and altered bandwidth estimates.

Algorithm Improvements

sskernel() / sskernel2d() — bandwidth optimization

• Log-spaced grid search (10 points, auto-expanding) followed by golden section refinement (up to 30 iterations) on the logexp-transformed scale. The two-stage approach combines the robustness of coarse grid search for multimodal landscapes with golden section precision — insensitive to grid resolution beyond 10 points (verified across 169 built-in R vectors/pairs + diamonds).
• 2D optimization is fully C++/OpenMP (compute_sskernel2d_cost_cpp, get_tau_bounds_cpp, compute_kde2d_cpp), handling isotropic Gaussian kernels with internal data standardization.

ssvkernel() — gamma optimization

• Multi-start golden section search (K=5 intervals over [0, 1]) with 30 iterations per start, guaranteeing at least one cost evaluation in every GS sub-interval. The MISE cost function is implemented in C++ with fused loops (no intermediate L×L matrix allocations) and runs in parallel across the K starts via OpenMP.
• Achieves ~100% global minimum detection across 35 diverse datasets, controlled by the ncores parameter.
• Window functions (Boxcar/Gauss/Laplace/Cauchy) ported from R to C++ inline functions, verified against Python/MATLAB reference with max_err ≤ 5.55e-17.

sskernel() / sskernel2d() / ssvkernel() — infrastructure

• logexp() / ilogexp() helpers extracted to common.R for the log-exp transformation required by golden section search.
• All four kernel functions (boxcar/laplace/cauchy/gauss) unified as C++ inline functions in sshist_algo.cpp, replacing separate R implementations.

Internal Cleanup

• R/ssvkernel.R: removed CostFunction() (dead code after C++ port of gamma optimization).
• R/common.R: removed kernel_boxcar(), kernel_laplace(), kernel_cauchy(), kernel_gauss() (replaced by C++ inline functions).
• R/sskernel.R: removed Rcpp export of test_kernels_cpp (was used only for kernel verification during development).

Documentation

• README.Rmd / README.md: High Performance bullet updated to reflect C++/OpenMP multi-start gamma optimisation and 2D kernel cost evaluation.
• vignettes/introduction.Rmd: ncores description now covers gamma optimisation (ssvkernel) and 2D kernel cost evaluation (sskernel2d); sskernel/sskernel2d descriptions mention two-stage grid + golden section search.
• man/sskernel2d.Rd / sskernel.Rd: description and parameters updated for the two-stage bandwidth search.

Testing

• Updated test expectations in test-ssvkernel.R for the corrected grid formula (53 instead of 256 points for waiting data) and new gamma optimisation algorithm.
• Updated reference values in test-sskernel_2d.R and test-ssvkernel_2d.R following golden section refinement in sskernel2d (changed pilot bandwidths and lambda factors).

sshist 0.2.4

Bug Fixes

• plot.sshist(): added freq = FALSE to histogram call so the plot correctly displays density instead of frequency.

sshist 0.2.3

Performance Improvements

• ssvkernel(): replaced iterative FFT smoothing with frequency-domain windowing using mvfft, reducing O(M²) FFT calls to O(M) matrix operations.
• ssvkernel(): vectorized which.min lookups and precomputed distance matrices for cost evaluation.
• ssvkernel() CostFunction: fully vectorized local bandwidth selection, replacing the for (k in 1:L) loop with max.col and matrix operations.
• ssvkernel(): removed unnecessary t() transpose in MVFFT slicing and unused weight_fun() helper.
• common.R: fixed edge case in fftkernel_1d where Lmax could be zero, ensured max(1, ...) guard.

Visual Improvements

• plot.sshist(): redesigned data display — jittered points and rug now sit in a reserved negative-y strip below the histogram bars (to avoid overlap).
• plot.sskernel() and plot.ssvkernel(): same reserved-strip approach for consistent look across all plot methods.
• All plot methods: redrawn y-axis showing only non-negative density ticks, with a subtle separator at y = 0.

New Features

• Added iris dataset tests for all six estimators with concrete reference values (278 total tests).

Documentation

• Added link references in README.

sshist 0.2.2

CRAN Compliance Fixes

• Removed invalid \cr from \describe{} in package documentation, fixing “LaTeX Error: There’s no line here to end.”
• Quoted OpenMP and backends in DESCRIPTION to avoid spelling NOTE on CRAN.

sshist 0.2.1

README Fixes

• Removed YAML frontmatter (output: github_document) from README.Rmd and README.md.

sshist 0.2.0

New Features

• Added sskernel() for optimal 1D fixed-bandwidth kernel density estimation.
• Added sskernel2d() for optimal 2D fixed-bandwidth kernel density estimation.
• Added ssvkernel() for locally adaptive 1D kernel density estimation (Shimazaki & Shinomoto 2010).
• Added ssvkernel2d() for locally adaptive 2D kernel density estimation (Abramson’s method).
• Added bootstrap confidence interval support for all kernel density estimators.
• Added C++ backends for 2D KDE cost computation, pilot density, and grid evaluation with OpenMP parallelism.
• Added ncores parameter to sshist() for multithreaded computation.

Algorithm Improvements

• Re-implemented sshist() with cleaner exhaustive search logic, exactly matching the original Python/MATLAB reference algorithms.
• Added resolution guard (anti-comb effect) with N_max = Range / (2 * Min_Resolution).
• Improved 2D histogram cost computation with pre-computed Y-bin indices for significant speedup.
• Added auto-expanding grid search for kernel bandwidth optimization.

Documentation

• Added vignettes: “Introduction to sshist” and “ggplot2 Visualization”.
• Added comprehensive S3 plot/print methods for all estimator classes.
• Updated README with complete function summary table.

Internal Changes

• Split code into modular R files: sshist.R, sskernel.R, ssvkernel.R, common.R.
• Updated to roxygen2 8.0 / Config/roxygen2/version format.
• Removed cost and n_tested fields from sshist return value (simplified output).
• Added C++ Rcpp functions: get_tau_bounds_cpp, compute_sskernel2d_cost_cpp, compute_pilot_density_cpp, compute_kde2d_cpp.

sshist 0.1.3

Algorithm Improvements

• Updated the binning resolution limit formula to N_max = Range / (2 * Min_Resolution) to prevent the “comb effect” (sampling artifacts). This change aligns the R implementation with the author’s reference code.
• The n_max parameter in sshist() is now strictly bounded by the resolution limit to prevent overfitting.

Documentation

• Fixed formatting in the DESCRIPTION file.
• Updated the faithful dataset examples in README.md to reflect the corrected optimal bin calculations (N changed from 37 to 21).
• Added CRAN download badges to README.md.
• Expanded reference links in README.md to include the original toolboxes and GitHub repositories from the algorithm’s authors.

sshist 0.1.2

CRAN Submission Fixes

• Fixed DESCRIPTION file reference formatting:
  • Added author names (Shimazaki and Shinomoto) to citation
  • Wrapped ‘C++’ in single quotes to comply with CRAN formatting requirements
• Improved documentation:
  • Added \value tags to all exported S3 method documentation files
  • Added comprehensive descriptions of return values and side effects for plot and print methods
  • Updated print methods to return objects invisibly following R best practices
  • Clear old images
• Fixed vignette:
  • Corrected graphical parameter handling in introduction.Rmd
  • Now properly stores and restores user’s par() settings

Internal Changes

• Added invisible(x) return statements to print.sshist() and print.sshist_2d() methods

sshist 0.1.1

Cosmetic fixes

• Fix installation links at Readme.Rmd.

sshist 0.1.0

• Initial CRAN submission.
• Added sshist() for 1D optimization (C++ optimized).
• Added sshist_2d() for 2D optimization.
• Added support for ggplot2 integration in examples.