update for CRAN

DESCRIPTION

@@ -12,7 +12,7 @@ Authors@R: c( person("Stavros", "Stavroglou", role = c("aut"),
                      email = "[email protected]",
                      comment = c(ORCID = "0009-0006-0095-0243")))
 Maintainer: Hui Wang <[email protected]>
-Description: A comprehensive package for detecting and analyzing causal relationships in complex systems using pattern-based approaches. Key features include state space reconstruction, pattern identification, and causality strength evaluation. Compared to existing packages: 'vars' provides linear vector autoregression but lacks nonlinear pattern detection; 'nonlinearTseries' offers general nonlinear analysis tools but no specific causality measures; 'rEDM' focuses on empirical dynamic modeling without pattern recognition; 'tseriesChaos' implements chaos theory methods but not pattern-based causality; 'CausalImpact' implements Bayesian structural time series models; 'pcalg' focuses on graphical causal models. This package uniquely combines these approaches with novel pattern recognition techniques for robust causality detection.
+Description: A comprehensive package for detecting and analyzing causal relationships in complex systems using pattern-based approaches. Key features include state space reconstruction, pattern identification, and causality strength evaluation.
 License: GPL-3 | file LICENSE
 Depends: R (>= 4.1.0)
 Imports: 

NAMESPACE

@@ -36,9 +36,7 @@ S3method(summary,pc_neighbors)
 S3method(summary,pc_params)
 S3method(summary,pc_state)
 export(distanceMetric)
-export(natureOfCausality)
 export(optimalParametersSearch)
-export(patternSpace)
 export(pcAccuracy)
 export(pcCrossMatrix)
 export(pcCrossValidation)
@@ -53,7 +51,6 @@ export(pc_params)
 export(plot_causality)
 export(plot_components)
 export(plot_total)
-export(signatureSpace)
 export(stateSpace)
 export(stateSpaceMethod)
 export(validate_custom_fn_output)

R/natureOfCausality.R

@@ -35,7 +35,8 @@
 #' \code{\link{pcFullDetails}} for detailed analysis
 #' \code{\link{pcMatrix}} for causality matrix computation
 #'
-#' @export
+#' @keywords internal
+#' @noRd
 #'
 #' @examples
 #' \donttest{

R/patternSpace.R

@@ -25,7 +25,8 @@
 #' patternSpaceMatrix <- patternSpace(signatureMatrix)
 #' print(patternSpaceMatrix)
 #'
-#' @export
+#' @keywords internal
+#' @noRd
 patternSpace <- function(SM) {
   # Input validation
   if (!is.matrix(SM) || !is.numeric(SM)) {

R/pattern_utils.R

@@ -1,3 +1,4 @@
+#' Print Pattern Causality Pattern Analysis Results
 #' @keywords internal
 #' @noRd
 print.pc_pattern <- function(x, ...) {
@@ -10,14 +11,14 @@ print.pc_pattern <- function(x, ...) {
 
 #' @keywords internal
 #' @noRd
-summary.pc_pattern <- function(x, ...) {
+summary.pc_pattern <- function(object, ...) {
   structure(
     list(
-      n_patterns = nrow(x$patterns),
-      dimension = ncol(x$patterns),
-      hash_range = range(x$hashes),
-      pattern_stats = summary(as.vector(x$patterns)),
-      hash_stats = summary(x$hashes)
+      n_patterns = nrow(object$patterns),
+      dimension = ncol(object$patterns),
+      hash_range = range(object$hashes),
+      pattern_stats = summary(as.vector(object$patterns)),
+      hash_stats = summary(object$hashes)
     ),
     class = "summary.pc_pattern"
   )

R/pc_full_details_utils.R

@@ -1,4 +1,4 @@
-#' Validate inputs for pattern causality analysis
+#' Validate Inputs for Pattern Causality Analysis
 #' @keywords internal
 #' @noRd
 validate_inputs <- function(X, Y, E, tau, metric, h, weighted, distance_fn = NULL) {
@@ -563,12 +563,45 @@ plot_causality.default <- function(x, type, ...) {
 
 #' Validate Custom Function Output
 #' 
-#' Validates the output format from custom distance and state space functions
+#' @title Validate Custom Function Output for Pattern Causality Analysis
+#' @description Validates the Output Format from Custom Distance and State Space Functions
+#' to ensure compatibility with the package's internal processing.
 #' 
 #' @param output The output from a custom function to validate
 #' @param fn_name The name of the function type being validated ("distance_fn" or "state_space_fn")
 #' @return Nothing. Throws an error if validation fails.
-#' @keywords internal
+#' 
+#' @examples
+#' # Example 1: Validating custom distance function output
+#' custom_dist <- function(x) {
+#'   # Create distance matrix
+#'   dist_mat <- as.matrix(dist(x))
+#'   # Validate output
+#'   validate_custom_fn_output(dist_mat, "distance_fn")
+#'   return(dist_mat)
+#' }
+#' 
+#' # Example 2: Validating custom state space function output
+#' custom_state_space <- function(x, E, tau) {
+#'   # Create state space matrix
+#'   n <- length(x) - (E-1)*tau
+#'   state_mat <- matrix(nrow = n, ncol = E)
+#'   for(i in 1:E) {
+#'     state_mat[,i] <- x[1:n + (i-1)*tau]
+#'   }
+#'   # Create output list
+#'   result <- list(matrix = state_mat, 
+#'                 parameters = list(E = E, tau = tau))
+#'   # Validate output
+#'   validate_custom_fn_output(result, "state_space_fn")
+#'   return(result)
+#' }
+#' 
+#' # Using the custom functions
+#' x <- sin(seq(0, 4*pi, length.out = 100))
+#' dist_result <- custom_dist(x)
+#' space_result <- custom_state_space(x, E = 3, tau = 2)
+#' 
 #' @export
 validate_custom_fn_output <- function(output, fn_name) {
   if(fn_name == "distance_fn" && !is.matrix(output)) {

R/pc_lightweight_utils.R

@@ -54,9 +54,8 @@ compute_causality_measures <- function(results, weighted) {
 
 #' Analyze Pattern Causality Between Time Series
 #' 
-#' @title Pattern Causality Analysis
-#' @description Internal function that performs the main causality analysis loop
-#' by analyzing patterns and signatures in reconstructed state spaces.
+#' @title Analyze Pattern Causality Between Time Series Using State Space Reconstruction
+#' @description Internal Function That Performs the Main Causality Analysis Loop
 #'
 #' @param spaces List containing state and pattern spaces
 #' @param matrices List containing initialized analysis matrices

R/signatureSpace.R

@@ -1,8 +1,8 @@
 #' Calculate Signature Space Matrix
 #' 
-#' @title Calculate Signature Space Matrix from State Space
-#' @description Calculates the signature space matrix from a state space matrix by 
-#' computing differences between successive elements in each row. This transformation 
+#' @title Calculate Signature Space Matrix From State Space
+#' @description Calculates the Signature Space Matrix From a State Space Matrix By 
+#' Computing Differences Between Successive Elements in Each Row. This transformation 
 #' helps capture the dynamic patterns in the time series data.
 #' 
 #' @param M A state space matrix where each row represents a point in state space
@@ -17,7 +17,8 @@
 #'   embedding functions, but this implementation is specifically tailored for 
 #'   pattern causality analysis.
 #' 
-#' @export
+#' @keywords internal
+#' @noRd
 signatureSpace <- function(M) {
   # Input validation
   if(!is.matrix(M)) {

inst/CITATION

@@ -8,6 +8,6 @@ bibentry(
     ),
     year     = "2024",
     note     = "Available at SSRN",
-    url      = "https://ssrn.com/abstract=4966221",
+    url      = "https://www.ssrn.com/abstract=4966221",
     doi      = "10.2139/ssrn.4966221"
 )