xiacf 0.6.2

CRAN Policy Compliance

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.