CharAnalysis v2.0.0 (R) — beta release

CharAnalysis 2.0.0 (beta)

First R implementation of CharAnalysis, a direct translation of
CharAnalysis v2.0 (MATLAB). Analytical outputs are validated against
four benchmark datasets; user testing is ongoing.

Please report issues at https://github.com/phiguera/CharAnalysis/issues.

New features relative to MATLAB v2.0

• Full R package with devtools::install_github() installation.
• CharAnalysis() returns a named list with S3 class "CharAnalysis";
  print(), summary(), and plot() methods are provided.
• Eight publication-quality ggplot2 figures (char_plot_peaks(),
  char_plot_fire_history(), char_plot_cumulative(), char_plot_fri(),
  char_plot_zones(), char_plot_raw(), char_plot_thresh_diag(),
  char_plot_sni()); save all to PDF with char_plot_all().
• char_write_results() writes the 33-column output matrix to CSV with
  column headers and numeric format matching the MATLAB output exactly.

Known differences from MATLAB v2.0

Robust lowess background (smoothing method 2). MATLAB's Curve Fitting
Toolbox smooth(..., 'rlowess') and the R char_lowess() port handle
NaN gaps differently inside the bisquare robustness iteration, producing
slightly different C_background series for records with missing values.
For gap-free records the difference is negligible (< 0.001); for records
with NaN gaps the maximum absolute difference across validated datasets
is 0.267 (Chickaree Lake). Smoothing method 1 (plain lowess) is
unaffected and agrees to within floating-point noise.

GMM peak counts. The Gaussian mixture model EM algorithm accumulates
floating-point arithmetic differently in R and MATLAB, causing slightly
different threshold values in some local windows. Peak counts differ by
10–20% across validated datasets, with the direction varying by dataset.

Figures 9 and 10. The threshold-sensitivity detail plot (Fig. 9) and
multi-site comparison plot (Fig. 10) from the MATLAB interface are not
implemented in this R package.

Smoothed FRI column (col 23). The R package computes smoothed
fire-return intervals in this column; MATLAB v2.0 stores NaN.

Validation summary

Dataset	Site	charBkg max|diff|	Peaks R	Peaks MATLAB
CO	Code Lake, AK	~5 × 10^-6^	39	48
CH10	Chickaree Lake, CO	0.267	59	50
SI17	Silver Lake, CO	0.130	25	31
RA07	Raven Lake, AK	< 0.001	15	17

Full validation details are in inst/z_Validation_report_R_vs_MATLAB_V_2.0.md.

Citation

If you use CharAnalysis in published research, please cite:

Higuera, P.E., L.B. Brubaker, P.M. Anderson, F.S. Hu, and T.A. Brown.
2009. Vegetation mediated the impacts of postglacial climate change on
fire regimes in the south-central Brooks Range, Alaska. Ecological
Monographs 79:201–219. https://doi.org/10.1890/07-2019.1

If you used Version 2.0 specifically, please also cite the software:

Higuera, P.E. 2026. CharAnalysis: Diagnostic and analytical tools for
peak analysis in sediment-charcoal records (Version 2.0). Zenodo.
https://doi.org/10.5281/zenodo.19304064

CharAnalysis Version 2.0

Since the mid-2000s, CharAnalysis has been used in dozens of published studies, with applications to sediment-charcoal records from across the globe. Version 2.0 is the first major update to the program, focusing entirely on modernizing the MATLAB codebase: eliminating legacy patterns, removing toolbox dependencies, and improving computational efficiency. The analytical methods are unchanged from Version 1.1.

CharAnalysis Version 1.1

Updates from CharAnalysis 1.0:

(1) Integrates SNI from Kelly et al. (2011)
(2) Compiled version (CharAnalysis*.exe) for Window 7, 64 bit machine.