xiacf 0.6.5

Resolved Armadillo Subview Memory Race Condition: Reverted the argument signature of xi_coefficient() from constant references (const arma::vec&) back to pass-by-value (arma::vec).
- Technical Details: Passing Armadillo’s subvec() (which returns a subview_col) to a constant vector reference forces Rcpp/Armadillo to implicitly generate a short-lived temporary object. In high-concurrency parallel environments (future.apply), the hyper-rapid creation and destruction of these temporaries generated memory race conditions and dangling pointers, leading to instant worker segmentation faults. Pass-by-value now safely enforces thread-isolated copies, ensuring 100% stability under intense parallel simulation loads without performance regression.

Unified Badge Visual Styles: Replaced native GitHub Actions and Zenodo SVG URLs in README.Rmd with unified rendering via shields.io. This bypasses GitHub’s Camo caching mechanism that frequently broke the Zenodo DOI badge visualization.
Upgraded Development Environment: Updated RoxygenNote in DESCRIPTION to version 8.0.0 and fully regenerated all manual (man/*.Rd) and namespace entries to clear stale macro warnings during compilation.

xiacf 0.6.4

Fixed a severe memory bottleneck by transforming xi_coefficient() arguments into const references, eliminating millions of redundant matrix deep copies during intensive loops.
Implemented memory-safe, in-place surrogate generation for univariate IAAFT (generate_single_iaaft_worker), preventing OOM-killer crashes in Linux parallel worker environments (future.apply).
Enhanced run_rolling_xi_acf and run_rolling_xi_ccf with strict input validation for time_index and explicit warning() tracking for failed windows.
Removed the memory-hazardous surrogate_miaaft_cpp C++ backend and replaced it with a safe R-level deprecated wrapper.

Fixed a critical bug where massive Monte Carlo simulations could cause a segmentation fault (exit code -11) due to floating-point rounding errors in C++.
Ensured MIAAFT surrogate generation strictly respects R’s global RNG state (e.g., set.seed()), enabling bit-for-bit reproducibility in parallel environments.

Strict CPU Core Limits: Updated the default core allocation in rolling functions (run_rolling_xi_acf, run_rolling_xi_ccf) to strictly comply with CRAN server policies (e.g., respecting MC_CORES and OMP_THREAD_LIMIT). Replaced parallel::detectCores() with max(1L, parallelly::availableCores() - 1L) to ensure safe execution without exceeding permitted limits or causing 0-core crashes.
Sequential Testing: Enforced strict sequential execution (future::plan(sequential)) via setup.R across the entire testthat suite to adhere to CRAN’s 2-core testing limit.

Fixed a bug in xi_matrix() where variable names (var_names) were inadvertently omitted from the output object, resulting in empty variable lists during print().
Unified the surrogate count FWER validation in xi_ccf() to utilize the centralized internal helper check_surrogate_count().
Cleaned up redundant "Error:" and "Warning:" prefixes in custom message strings across the package to ensure native R console formatting.
Removed unreachable dead code regarding duplicate sig_level validation in xi_matrix().

Exposed the max_iter argument in run_rolling_xi_acf() and run_rolling_xi_ccf(), allowing users to explicitly tune the maximum number of iterations for the IAAFT/MIAAFT surrogate convergence.
Simplified and standardized the linear ACF confidence interval mathematical formula in xi_acf().

Core Math Fix: Corrected the denominator in the internal C++ implementation of Chatterjee’s Xi coefficient to exactly \(n^2 - 1\). This fixes an issue where the baseline for independent variables was slightly inflated (approx. 0.33) rather than asymptotically converging to 0. (Thanks to user reports and rigorous auditing).
Dual-Family FWER Control: Introduced a mathematically rigorous separation of FWER control families in xi_ccf and xi_matrix. The Max-Statistic null distribution is now strictly evaluated independently for Contemporaneous (Lag 0) and Temporal (Lag > 0) dependencies. This resolves the “Lag-0 Masking Effect,” significantly improving the statistical power to detect delayed causal propagation.
Autocorrelation Exclusion: Excluded completely diagonal elements (autocorrelations) from the FWER search space in xi_matrix to prevent arbitrary threshold inflation.

Improved parallel backend safety using %dofuture% with explicit package loading.
Restored the Window_ID tracking column in the outputs of run_rolling_xi_acf and run_rolling_xi_ccf.
Upgraded internal surrogate generation checks (check_surrogate_count) to rigorously validate user-provided n_surr against the dynamic size of FWER test families.

Directional Separation: xi_ccf() now explicitly separates causal directions (direction = "both", "x_leads", "y_leads") and returns Tidy data frames for easier downstream EDA.
Enhanced FWER Control: Excluded self-loops (autocorrelations) from the xi_matrix() Max-Statistic empirical null distribution, restoring statistical power for detecting true cross-edge pathways.
Lag 0 Synchronization: Included contemporaneous effects (Lag 0) in xi_matrix() C++ calculations to synchronize behavior with xi_ccf().
On-demand Thresholds: Updated extraction functions (extract_xi_acf(), extract_xi_ccf()) to dynamically recompute exact FWER thresholds using preserved raw data (data_raw).
Unified Plotting Aesthetics: Redesigned autoplot() methods for xi_ccf (vertical faceting) and xi_matrix (diagonal variable labels) to provide publication-ready, unified Tidyverse compatibility.
Bug Fixes: Fixed a C++ segmentation fault related to Lag 0 memory allocation, and resolved a Non-Standard Evaluation (NSE) bug in extractors that caused messy facet labels.
Test Suite Overhaul: Expanded and strictly validated the new tidy structures and directional logic (58 tests passing).

FWER Control: Implemented strict Family-Wise Error Rate (‘FWER’) control via Max-statistic across all core functions (xi_acf, xi_ccf, xi_matrix).
Performance: Refactored core engines using C++ (RcppArmadillo) for MIAAFT and IAAFT surrogate generation, significantly improving computational speed.
Visualization: Enhanced autoplot methods to produce publication-ready ggplot2 charts utilizing base R expression() for native math rendering.
Compatibility: Improved backward compatibility to smoothly transition legacy sig_level = 0.95 (confidence level) inputs to significance levels, and systematically deprecated older functions with proper warnings.

Fixed a potential C++ RNG synchronization issue by delegating RNG state management entirely to Rcpp::RNGScope.