Style with air (#862)

Author: strengejacke

DESCRIPTION

@@ -159,7 +159,7 @@ Suggests:
     withr (>= 3.0.0)
 Encoding: UTF-8
 Language: en-US
-RoxygenNote: 7.3.2
+RoxygenNote: 7.3.3
 Roxygen: list(markdown = TRUE)
 Config/testthat/edition: 3
 Config/testthat/parallel: true

R/binned_residuals.R

@@ -75,16 +75,18 @@
 #' }
 #'
 #' @export
-binned_residuals <- function(model,
-                             term = NULL,
-                             n_bins = NULL,
-                             show_dots = NULL,
-                             ci = 0.95,
-                             ci_type = "exact",
-                             residuals = "deviance",
-                             iterations = 1000,
-                             verbose = TRUE,
-                             ...) {
+binned_residuals <- function(
+  model,
+  term = NULL,
+  n_bins = NULL,
+  show_dots = NULL,
+  ci = 0.95,
+  ci_type = "exact",
+  residuals = "deviance",
+  iterations = 1000,
+  verbose = TRUE,
+  ...
+) {
   ci_type <- insight::validate_argument(
     ci_type,
     c("exact", "gaussian", "boot")
@@ -98,7 +100,9 @@ binned_residuals <- function(model,
   if (isFALSE(insight::model_info(model)$is_bernoulli)) {
     ci_type <- "gaussian"
     if (verbose) {
-      insight::format_alert("Using `ci_type = \"gaussian\"` because model is not bernoulli.")
+      insight::format_alert(
+        "Using `ci_type = \"gaussian\"` because model is not bernoulli."
+      )
     }
   }
 
@@ -121,18 +125,23 @@ binned_residuals <- function(model,
   y0 <- .recode_to_zero(insight::get_response(model, verbose = FALSE))
 
   # calculate residuals
-  y <- switch(residuals,
+  y <- switch(
+    residuals,
     response = y0 - fitted_values,
     pearson = .safe((y0 - fitted_values) / sqrt(fitted_values * (1 - fitted_values))),
     deviance = .safe(stats::residuals(model, type = "deviance"))
   )
 
   # make sure we really have residuals
   if (is.null(y)) {
-    insight::format_error("Could not calculate residuals. Try using `residuals = \"response\"`.")
+    insight::format_error(
+      "Could not calculate residuals. Try using `residuals = \"response\"`."
+    )
   }
 
-  if (is.null(n_bins)) n_bins <- round(sqrt(length(pred)))
+  if (is.null(n_bins)) {
+    n_bins <- round(sqrt(length(pred)))
+  }
 
   breaks.index <- floor(length(pred) * (1:(n_bins - 1)) / n_bins)
   breaks <- unique(c(-Inf, sort(pred)[breaks.index], Inf))
@@ -151,8 +160,13 @@ binned_residuals <- function(model,
     if (n == 0) {
       conf_int <- stats::setNames(c(NA, NA), c("CI_low", "CI_high"))
     } else {
-      conf_int <- switch(ci_type,
-        gaussian = stats::qnorm(c((1 - ci) / 2, (1 + ci) / 2), mean = ybar, sd = sdev / sqrt(n)),
+      conf_int <- switch(
+        ci_type,
+        gaussian = stats::qnorm(
+          c((1 - ci) / 2, (1 + ci) / 2),
+          mean = ybar,
+          sd = sdev / sqrt(n)
+        ),
         exact = {
           out <- stats::binom.test(sum(y0[items]), n)$conf.int
           # center CIs around point estimate

R/check_autocorrelation.R

@@ -53,7 +53,9 @@ check_autocorrelation.default <- function(x, nsim = 1000, ...) {
 
 #' @export
 plot.check_autocorrelation <- function(x, ...) {
-  insight::format_warning("There is currently no `plot()` method for `check_autocorrelation()`.")
+  insight::format_warning(
+    "There is currently no `plot()` method for `check_autocorrelation()`."
+  )
 }
 
 

R/check_clusterstructure.R

@@ -37,10 +37,7 @@
 #'   assessment of (cluster) tendency. In Proceedings of the 2002 International
 #'   Joint Conference on Neural Networks. IJCNN02 (3), 2225-2230. IEEE.
 #' @export
-check_clusterstructure <- function(x,
-                                   standardize = TRUE,
-                                   distance = "euclidean",
-                                   ...) {
+check_clusterstructure <- function(x, standardize = TRUE, distance = "euclidean", ...) {
   if (standardize) {
     x <- as.data.frame(scale(x))
   }
@@ -64,13 +61,22 @@ check_clusterstructure <- function(x,
 
   out <- list(
     H = H,
-    dissimilarity_matrix = .clusterstructure_dm(x, distance = distance, method = "ward.D2")
+    dissimilarity_matrix = .clusterstructure_dm(
+      x,
+      distance = distance,
+      method = "ward.D2"
+    )
   )
 
   attr(out, "text") <- res_text
   attr(out, "color") <- color
   attr(out, "title") <- "Clustering tendency"
-  class(out) <- c("see_check_clusterstructure", "check_clusterstructure", "easystats_check", class(out))
+  class(out) <- c(
+    "see_check_clusterstructure",
+    "check_clusterstructure",
+    "easystats_check",
+    class(out)
+  )
   out
 }
 
@@ -80,8 +86,10 @@ plot.check_clusterstructure <- function(x, ...) {
   # Can be reimplemented with ggplot in see
   stats::heatmap(
     x$dissimilarity_matrix,
-    Rowv = NA, Colv = NA,
-    labRow = FALSE, labCol = FALSE,
+    Rowv = NA,
+    Colv = NA,
+    labRow = FALSE,
+    labCol = FALSE,
     col = grDevices::colorRampPalette(c("#2196F3", "#FAFAFA", "#E91E63"))(100)
   )
 }

R/check_collinearity.R

@@ -313,11 +313,13 @@ check_collinearity.betamfx <- check_collinearity.logitor
 
 #' @rdname check_collinearity
 #' @export
-check_collinearity.glmmTMB <- function(x,
-                                       component = "all",
-                                       ci = 0.95,
-                                       verbose = TRUE,
-                                       ...) {
+check_collinearity.glmmTMB <- function(
+  x,
+  component = "all",
+  ci = 0.95,
+  verbose = TRUE,
+  ...
+) {
   component <- insight::validate_argument(
     component,
     c("all", "conditional", "count", "zi", "zero_inflated")
@@ -327,11 +329,13 @@ check_collinearity.glmmTMB <- function(x,
 
 
 #' @export
-check_collinearity.MixMod <- function(x,
-                                      component = "all",
-                                      ci = 0.95,
-                                      verbose = TRUE,
-                                      ...) {
+check_collinearity.MixMod <- function(
+  x,
+  component = "all",
+  ci = 0.95,
+  verbose = TRUE,
+  ...
+) {
   component <- insight::validate_argument(
     component,
     c("all", "conditional", "count", "zi", "zero_inflated")
@@ -341,11 +345,13 @@ check_collinearity.MixMod <- function(x,
 
 
 #' @export
-check_collinearity.hurdle <- function(x,
-                                      component = "all",
-                                      ci = 0.95,
-                                      verbose = verbose,
-                                      ...) {
+check_collinearity.hurdle <- function(
+  x,
+  component = "all",
+  ci = 0.95,
+  verbose = verbose,
+  ...
+) {
   component <- insight::validate_argument(
     component,
     c("all", "conditional", "count", "zi", "zero_inflated")
@@ -355,11 +361,13 @@ check_collinearity.hurdle <- function(x,
 
 
 #' @export
-check_collinearity.zeroinfl <- function(x,
-                                        component = "all",
-                                        ci = 0.95,
-                                        verbose = verbose,
-                                        ...) {
+check_collinearity.zeroinfl <- function(
+  x,
+  component = "all",
+  ci = 0.95,
+  verbose = verbose,
+  ...
+) {
   component <- insight::validate_argument(
     component,
     c("all", "conditional", "count", "zi", "zero_inflated")
@@ -369,11 +377,13 @@ check_collinearity.zeroinfl <- function(x,
 
 
 #' @export
-check_collinearity.zerocount <- function(x,
-                                         component = "all",
-                                         ci = 0.95,
-                                         verbose = verbose,
-                                         ...) {
+check_collinearity.zerocount <- function(
+  x,
+  component = "all",
+  ci = 0.95,
+  verbose = verbose,
+  ...
+) {
   component <- insight::validate_argument(
     component,
     c("all", "conditional", "count", "zi", "zero_inflated")
@@ -385,11 +395,17 @@ check_collinearity.zerocount <- function(x,
 # utilities ---------------------------------
 
 .check_collinearity_zi_model <- function(x, component, ci = 0.95, verbose = TRUE) {
-  if (component == "count") component <- "conditional"
-  if (component == "zi") component <- "zero_inflated"
+  if (component == "count") {
+    component <- "conditional"
+  }
+  if (component == "zi") {
+    component <- "zero_inflated"
+  }
 
   mi <- insight::model_info(x, verbose = FALSE)
-  if (!mi$is_zero_inflated) component <- "conditional"
+  if (!mi$is_zero_inflated) {
+    component <- "conditional"
+  }
 
   if (component == "all") {
     cond <- .check_collinearity(x, "conditional", ci = ci, verbose = verbose)
@@ -439,7 +455,10 @@ check_collinearity.zerocount <- function(x,
     if (isTRUE(verbose)) {
       insight::format_alert(
         paste(
-          sprintf("Could not extract the variance-covariance matrix for the %s component of the model.", component),
+          sprintf(
+            "Could not extract the variance-covariance matrix for the %s component of the model.",
+            component
+          ),
           "Please try to run `vcov(model)`, which may help identifying the problem."
         )
       )
@@ -453,13 +472,15 @@ check_collinearity.zerocount <- function(x,
   if (is.null(term_assign) || all(is.na(term_assign))) {
     if (verbose) {
       insight::format_alert(
-        sprintf("Could not extract model terms for the %s component of the model.", component)
+        sprintf(
+          "Could not extract model terms for the %s component of the model.",
+          component
+        )
       )
     }
     return(NULL)
   }
 
-
   # we have rank-deficiency here. remove NA columns from assignment
   if (isTRUE(attributes(v)$rank_deficient) && !is.null(attributes(v)$na_columns_index)) {
     term_assign <- term_assign[-attributes(v)$na_columns_index]
@@ -482,9 +503,11 @@ check_collinearity.zerocount <- function(x,
 
   # hurdle or zeroinfl model can have no zero-inflation formula, in which case
   # we have the same formula as for conditional formula part
-  if (inherits(x, c("hurdle", "zeroinfl", "zerocount")) &&
-    component == "zero_inflated" &&
-    is.null(f[["zero_inflated"]])) {
+  if (
+    inherits(x, c("hurdle", "zeroinfl", "zerocount")) &&
+      component == "zero_inflated" &&
+      is.null(f[["zero_inflated"]])
+  ) {
     f$zero_inflated <- f$conditional
   }
 
@@ -503,7 +526,10 @@ check_collinearity.zerocount <- function(x,
   if (n.terms < 2) {
     if (isTRUE(verbose)) {
       insight::format_alert(
-        sprintf("Not enough model terms in the %s part of the model to check for multicollinearity.", component)
+        sprintf(
+          "Not enough model terms in the %s part of the model to check for multicollinearity.",
+          component
+        )
       )
     }
     return(NULL)
@@ -639,17 +665,20 @@ check_collinearity.zerocount <- function(x,
   tryCatch(
     {
       if (inherits(x, c("hurdle", "zeroinfl", "zerocount"))) {
-        term_assign <- switch(component,
+        term_assign <- switch(
+          component,
           conditional = attr(insight::get_modelmatrix(x, model = "count"), "assign"),
           zero_inflated = attr(insight::get_modelmatrix(x, model = "zero"), "assign")
         )
       } else if (inherits(x, "glmmTMB")) {
-        term_assign <- switch(component,
+        term_assign <- switch(
+          component,
           conditional = attr(insight::get_modelmatrix(x), "assign"),
           zero_inflated = .zi_term_assignment(x, component, verbose = verbose)
         )
       } else if (inherits(x, "MixMod")) {
-        term_assign <- switch(component,
+        term_assign <- switch(
+          component,
           conditional = attr(insight::get_modelmatrix(x, type = "fixed"), "assign"),
           zero_inflated = attr(insight::get_modelmatrix(x, type = "zi_fixed"), "assign")
         )
@@ -692,7 +721,10 @@ check_collinearity.zerocount <- function(x,
   }))
 
   if (insight::is_gam_model(x)) {
-    model_params <- as.vector(unlist(insight::find_parameters(x)[c(component, "smooth_terms")]))
+    model_params <- as.vector(unlist(insight::find_parameters(x)[c(
+      component,
+      "smooth_terms"
+    )]))
   } else {
     model_params <- insight::find_parameters(x)[[component]]
   }