easystats · etiennebacher · Oct 8, 2025
diff --git a/.Rbuildignore b/.Rbuildignore
@@ -52,3 +52,4 @@ references.bib
 ^revdep$
 ^CRAN-SUBMISSION$
 ^LICENSE\.md$
+^[.]?air[.]toml$
diff --git a/R/cor_lower.R b/R/cor_lower.R
@@ -45,7 +45,10 @@ cor_lower.easycorrelation <- function(x, diag = FALSE, ...) {
   for (param1 in rownames(m)) {
     for (param2 in colnames(m)) {
       if (tri[param1, param2]) {
-        tokeep <- c(tokeep, which(x$Parameter1 == param1 & x$Parameter2 == param2))
+        tokeep <- c(
+          tokeep,
+          which(x$Parameter1 == param1 & x$Parameter2 == param2)
+        )
       }
     }
   }

diff --git a/R/cor_smooth.R b/R/cor_smooth.R
@@ -30,47 +30,66 @@ cor_smooth <- function(x, method = "psych", verbose = TRUE, ...) {
 
 
 #' @export
-cor_smooth.easycorrelation <- function(x,
-                                       method = "psych",
-                                       verbose = TRUE,
-                                       tol = 10^-12,
-                                       ...) {
-  m <- cor_smooth(as.matrix(x), method = method, verbose = verbose, tol = tol, ...)
+cor_smooth.easycorrelation <- function(
+  x,
+  method = "psych",
+  verbose = TRUE,
+  tol = 10^-12,
+  ...
+) {
+  m <- cor_smooth(
+    as.matrix(x),
+    method = method,
+    verbose = verbose,
+    tol = tol,
+    ...
+  )
 
   if (isTRUE(attributes(m)$smoothed)) {
     estim <- names(x)[names(x) %in% c("r", "rho", "tau", "D")][1]
 
     for (param1 in row.names(m)) {
       for (param2 in colnames(m)) {
-        if (nrow(x[x$Parameter1 == param1 & x$Parameter2 == param2, ]) == 0) next
+        if (nrow(x[x$Parameter1 == param1 & x$Parameter2 == param2, ]) == 0) {
+          next
+        }
         # Print changes
         if (verbose) {
           val1 <- x[x$Parameter1 == param1 & x$Parameter2 == param2, estim]
           val2 <- m[param1, param2]
           if (round(val1 - val2, digits = 2) == 0) {
-            insight::print_color(paste0(
-              param1,
-              " - ",
-              param2,
-              ": no change (",
-              insight::format_value(val1),
-              ")\n"
-            ), "green")
+            insight::print_color(
+              paste0(
+                param1,
+                " - ",
+                param2,
+                ": no change (",
+                insight::format_value(val1),
+                ")\n"
+              ),
+              "green"
+            )
           } else {
-            insight::print_color(paste0(
-              param1,
-              " - ",
-              param2,
-              ": ",
-              insight::format_value(val1),
-              " -> ",
-              insight::format_value(val2),
-              "\n"
-            ), "red")
+            insight::print_color(
+              paste0(
+                param1,
+                " - ",
+                param2,
+                ": ",
+                insight::format_value(val1),
+                " -> ",
+                insight::format_value(val2),
+                "\n"
+              ),
+              "red"
+            )
           }
           cat("\n")
         }
-        x[x$Parameter1 == param1 & x$Parameter2 == param2, estim] <- m[param1, param2]
+        x[x$Parameter1 == param1 & x$Parameter2 == param2, estim] <- m[
+          param1,
+          param2
+        ]
       }
     }
 
@@ -87,24 +106,31 @@ cor_smooth.easycorrelation <- function(x,
 
 
 #' @export
-cor_smooth.matrix <- function(x,
-                              method = "psych",
-                              verbose = TRUE,
-                              tol = 10^-12,
-                              ...) {
+cor_smooth.matrix <- function(
+  x,
+  method = "psych",
+  verbose = TRUE,
+  tol = 10^-12,
+  ...
+) {
   method <- match.arg(method, choices = c("psych", "hj", "lrs"))
 
   # Already positive definite
   if (is.positive_definite(x, tol = tol, ...)) {
-    if (verbose) message("Matrix is positive definite, smoothing was not needed.")
+    if (verbose) {
+      message("Matrix is positive definite, smoothing was not needed.")
+    }
     return(x)
   }
 
   if (method == "psych") {
     insight::check_if_installed("psych")
     x <- suppressWarnings(psych::cor.smooth(x, eig.tol = tol, ...))
   } else {
-    out <- try(suppressMessages(mbend::bend(x, method = method, ...)), silent = TRUE)
+    out <- try(
+      suppressMessages(mbend::bend(x, method = method, ...)),
+      silent = TRUE
+    )
     if (inherits(out, "try-error")) {
       return(x)
     }
@@ -134,9 +160,12 @@ is.positive_definite.matrix <- function(x, tol = 10^-12, ...) {
 
   # validation checks
   if (inherits(eigens, "try-error")) {
-    stop(insight::format_message(
-      "There is something seriously wrong with the correlation matrix, as some of the eigen values are NA."
-    ), call. = FALSE)
+    stop(
+      insight::format_message(
+        "There is something seriously wrong with the correlation matrix, as some of the eigen values are NA."
+      ),
+      call. = FALSE
+    )
   }
 
   # Find out

diff --git a/R/cor_sort.R b/R/cor_sort.R
@@ -20,13 +20,28 @@
 #' cor_sort(x, hclust_method = "ward.D2") # It can also reorder the long form output
 #' cor_sort(summary(x, redundant = TRUE)) # As well as from the summary
 #' @export
-cor_sort <- function(x, distance = "correlation", hclust_method = "complete", ...) {
+cor_sort <- function(
+  x,
+  distance = "correlation",
+  hclust_method = "complete",
+  ...
+) {
   UseMethod("cor_sort")
 }
 
 #' @export
-cor_sort.easycorrelation <- function(x, distance = "correlation", hclust_method = "complete", ...) {
-  m <- cor_sort(as.matrix(x), distance = distance, hclust_method = hclust_method, ...)
+cor_sort.easycorrelation <- function(
+  x,
+  distance = "correlation",
+  hclust_method = "complete",
+  ...
+) {
+  m <- cor_sort(
+    as.matrix(x),
+    distance = distance,
+    hclust_method = hclust_method,
+    ...
+  )
   x$Parameter1 <- factor(x$Parameter1, levels = rownames(m))
   x$Parameter2 <- factor(x$Parameter2, levels = colnames(m))
   reordered <- x[order(x$Parameter1, x$Parameter2), ]
@@ -48,7 +63,12 @@ cor_sort.easycorrelation <- function(x, distance = "correlation", hclust_method
 
 
 #' @export
-cor_sort.easycormatrix <- function(x, distance = "correlation", hclust_method = "complete", ...) {
+cor_sort.easycormatrix <- function(
+  x,
+  distance = "correlation",
+  hclust_method = "complete",
+  ...
+) {
   if (!"Parameter" %in% colnames(x)) {
     return(NextMethod())
   }
@@ -60,7 +80,9 @@ cor_sort.easycormatrix <- function(x, distance = "correlation", hclust_method =
 
   # If non-redundant matrix, fail (## TODO: fix that)
   if (anyNA(m)) {
-    insight::format_error("Non-redundant matrices are not supported yet. Try again by setting summary(..., redundant = TRUE)")
+    insight::format_error(
+      "Non-redundant matrices are not supported yet. Try again by setting summary(..., redundant = TRUE)"
+    )
   }
 
   # Get sorted matrix
@@ -77,9 +99,22 @@ cor_sort.easycormatrix <- function(x, distance = "correlation", hclust_method =
   )
 
   # Reorder attributes (p-values) etc.
-  for (id in c("p", "CI", "CI_low", "CI_high", "BF", "Method", "n_Obs", "df_error", "t")) {
+  for (id in c(
+    "p",
+    "CI",
+    "CI_low",
+    "CI_high",
+    "BF",
+    "Method",
+    "n_Obs",
+    "df_error",
+    "t"
+  )) {
     if (id %in% names(attributes(reordered))) {
-      attributes(reordered)[[id]] <- attributes(reordered)[[id]][order(x$Parameter), names(reordered)]
+      attributes(reordered)[[id]] <- attributes(reordered)[[id]][
+        order(x$Parameter),
+        names(reordered)
+      ]
     }
   }
 
@@ -91,9 +126,19 @@ cor_sort.easycormatrix <- function(x, distance = "correlation", hclust_method =
 
 
 #' @export
-cor_sort.matrix <- function(x, distance = "correlation", hclust_method = "complete", ...) {
+cor_sort.matrix <- function(
+  x,
+  distance = "correlation",
+  hclust_method = "complete",
+  ...
+) {
   if (isSquare(x) && all(colnames(x) %in% rownames(x))) {
-    i <- .cor_sort_square(x, distance = distance, hclust_method = hclust_method, ...)
+    i <- .cor_sort_square(
+      x,
+      distance = distance,
+      hclust_method = hclust_method,
+      ...
+    )
   } else {
     i <- .cor_sort_nonsquare(x, distance = "euclidean", ...)
   }
@@ -111,8 +156,12 @@ cor_sort.matrix <- function(x, distance = "correlation", hclust_method = "comple
 
 # Utils -------------------------------------------------------------------
 
-
-.cor_sort_square <- function(m, distance = "correlation", hclust_method = "complete", ...) {
+.cor_sort_square <- function(
+  m,
+  distance = "correlation",
+  hclust_method = "complete",
+  ...
+) {
   if (distance == "correlation") {
     d <- stats::as.dist((1 - m) / 2) # r = -1 -> d = 1; r = 1 -> d = 0
   } else if (distance == "raw") {