Changes in version 2026.2 (2026-02-26)                 

  - Minor changes and improvements.

                Changes in version 2025.11 (2025-11-24)                 

  - Improved DPI_dag() and plot.dpi.dag(). Also forced the plot to
    strictly show a DAG while changing edge color of insignificant DPI
    into faded grey.
  - (Fixed in patch version 2025.10-1) Fixed DPI_curve() for wrong
    (reverse) direction of DPI caused by the change of parameter order
    of x and y in version 2025.10.
  - (Fixed in patch version 2025.10-1) Fixed a bug caused by dpi
    parameter-object name conflict (internally) when saving DPI()
    results into a file.

                Changes in version 2025.10 (2025-10-16)                 

This version contains breaking changes to function names and
visualization methods.

  - Added DPI_dag(): Directed acyclic graphs (DAGs) via DPI exploratory
    analysis (causal discovery) for all significant partial
    correlations.
  - Added bonf and pseudoBF parameters to DPI(), DPI_curve(), and
    DPI_dag().
      - bonf: Bonferroni correction to control for false positive rates
        among multiple pairwise DPI tests.
      - pseudoBF: Use normalized pseudo Bayes Factors
        sigmoid(log(PseudoBF10)) as the Significance score (0~1). Pseudo
        Bayes Factors are computed using the transformation rules
        proposed by Wagenmakers (2022)
        https://doi.org/10.31234/osf.io/egydq.
  - Added S3 methods plot.cor.net(), plot.bns.dag(), and plot.dpi.dag()
    that can transform qgraph base-plot objects into ggplot objects for
    more stable and flexible visualization.
  - Added p_to_bf(): Convert p values to pseudo Bayes Factors
    ($\text{PseudoBF}_{10}$).
  - Renamed cor_network() to cor_net(), dag_network() to BNs_dag(), and
    matrix_cor() to cor_matrix().
  - Fixed cor_net() to return the exactly correct p values of (partial)
    correlation coefficients.
  - Improved output information in console and plot.

                 Changes in version 2025.9 (2025-09-20)                 

This version contains breaking changes to both algorithm and
functionality.

  - Refined DPI() algorithm to limit $\text{DPI} \in (-1, 1)$ and also
    simplified its output information. $$ \begin{aligned} \text{DPI}{X
    \rightarrow Y} & = \text{Direction}{X \rightarrow Y} \cdot
    \text{Significance}{X \rightarrow Y} \ & = \text{Delta}(R^2) \cdot
    \text{Sigmoid}(\frac{p}{\alpha}) \ & = \left( R{Y \sim X + Covs}^2 -
    R_{X \sim Y + Covs}^2 \right) \cdot \left( 1 - \tanh
    \frac{p_{XY|Covs}}{2\alpha} \right) \ & \in (-1, 1) \end{aligned} $$
      - In an earlier version of algorithm, the strength score was
        computed as $t_{\beta_{XY|Covs}}^2 = t_{r.partial_{XY|Covs}}^2
        \in [0, +\infty)$. While this algorithm performs as well as the
        new $\text{Sigmoid}(\frac{p}{\alpha})$ approach (e.g., both have
        low false positive and false negative rates), $t^2$ has a major
        flaw that its values cannot converge to a limited range so that
        the final DPI values would be heavily determined by $t^2$, which
        is not a desired attribute. In contrast, the new algorithm can
        make the significance score more likely to be an "on-off
        switch", with values more likely approximating 0 or 1, thereby
        minimizing its impact on the interpretation of final DPI values.
  - Renamed data_random() to sim_data() with enhanced functionality that
    supports data simulation from a multivariate normal distribution,
    using MASS::mvrnorm().
  - Added sim_data_exp(): Simulate experiment-like data with independent
    binary Xs.
  - Used gc() in DPI(), DPI_curve(), and dag_network() for memory
    garbage collection.
  - Provided a better example in dag_network() for arranging multiple
    base-R-style plots using aplot::plot_list().

                 Changes in version 2025.8 (2025-08-20)                 

  - Added dag_network(): Directed acyclic graphs (DAGs) via causal
    Bayesian networks (BNs).
  - Improved cor_network(): Correlation and partial correlation
    networks.
  - Moved help pages of all S3 method functions to S3method.dpi and
    S3method.network and made them as internal topics.

                 Changes in version 2025.6 (2025-06-18)                 

  - CRAN package publication.
  - Initial public release on GitHub.
  - Developed core functions and package logo.