lintr

R/smoothness.R

@@ -39,15 +39,13 @@ smoothness.numeric <- function(x,
   }
 
   if (method == "cor") {
-    smooth <- stats::cor(utils::head(x, length(x) - lag), utils::tail(x, length(x) - lag))
+    smooth_data <- stats::cor(utils::head(x, length(x) - lag), utils::tail(x, length(x) - lag))
   } else {
-    smooth <- stats::sd(diff(x, lag = lag)) / abs(mean(diff(x, lag = lag)))
+    smooth_data <- stats::sd(diff(x, lag = lag)) / abs(mean(diff(x, lag = lag)))
   }
 
   if (!is.null(iterations)) {
-    if (!requireNamespace("boot", quietly = TRUE)) {
-      insight::format_warning("Package 'boot' needed for bootstrapping SEs.")
-    } else {
+    if (requireNamespace("boot", quietly = TRUE)) {
       results <- boot::boot(
         data = x,
         statistic = .boot_smoothness,
@@ -56,12 +54,14 @@ smoothness.numeric <- function(x,
         lag = lag
       )
       out_se <- stats::sd(results$t, na.rm = TRUE)
-      smooth <- data.frame(Smoothness = smooth, SE = out_se)
+      smooth_data <- data.frame(Smoothness = smooth_data, SE = out_se)
+    } else {
+      insight::format_warning("Package 'boot' needed for bootstrapping SEs.")
     }
   }
 
-  class(smooth) <- unique(c("parameters_smoothness", class(smooth)))
-  smooth
+  class(smooth_data) <- unique(c("parameters_smoothness", class(smooth_data)))
+  smooth_data
 }
 
 

R/standardize.models.R

@@ -107,9 +107,9 @@ standardize.default <- function(x,
                                 update_expr,
                                 ...) {
   m_info <- .get_model_info(x, ...)
-  data <- insight::get_data(x, source = "mf", verbose = FALSE)
+  model_data <- insight::get_data(x, source = "mf", verbose = FALSE)
 
-  if (isTRUE(attr(data, "is_subset"))) {
+  if (isTRUE(attr(model_data, "is_subset"))) {
     insight::format_error("Cannot standardize a model fit with a 'subset = '.")
   }
 
@@ -164,10 +164,10 @@ standardize.default <- function(x,
   weight_variable <- insight::find_weights(x)
 
   if (!is.null(weight_variable) &&
-    !weight_variable %in% colnames(data) &&
-    "(weights)" %in% colnames(data)) {
-    data$.missing_weight <- data[["(weights)"]]
-    colnames(data)[ncol(data)] <- weight_variable
+    !weight_variable %in% colnames(model_data) &&
+    "(weights)" %in% colnames(model_data)) {
+    model_data$.missing_weight <- model_data[["(weights)"]]
+    colnames(model_data)[ncol(model_data)] <- weight_variable
     weight_variable <- c(weight_variable, "(weights)")
   }
 
@@ -178,12 +178,12 @@ standardize.default <- function(x,
   ## ---- SUMMARY: TO Z OR NOT TO Z? ----
 
   dont_standardize <- c(resp, weight_variable, random_group_factor)
-  do_standardize <- setdiff(colnames(data), dont_standardize)
+  do_standardize <- setdiff(colnames(model_data), dont_standardize)
 
   # can't std data$var variables
   doller_vars <- grepl("(.*)\\$(.*)", do_standardize)
   if (any(doller_vars)) {
-    doller_vars <- colnames(data)[doller_vars]
+    doller_vars <- colnames(model_data)[doller_vars]
     insight::format_warning(
       "Unable to standardize variables evaluated in the environment (i.e., not in `data`).",
       "The following variables will not be standardizd:",
@@ -204,7 +204,7 @@ standardize.default <- function(x,
 
   w <- insight::get_weights(x, remove_na = TRUE)
 
-  data_std <- standardize(data[do_standardize],
+  data_std <- standardize(model_data[do_standardize],
     robust = robust,
     two_sd = two_sd,
     weights = if (weights) w,
@@ -213,7 +213,7 @@ standardize.default <- function(x,
 
   # if two_sd, it must not affect the response!
   if (include_response && two_sd) {
-    data_std[resp] <- standardize(data[resp],
+    data_std[resp] <- standardize(model_data[resp],
       robust = robust,
       two_sd = FALSE,
       weights = if (weights) w,
@@ -254,8 +254,8 @@ standardize.default <- function(x,
 
   ## ---- ADD BACK VARS THAT WHERE NOT Z ----
   if (length(dont_standardize)) {
-    remaining_columns <- intersect(colnames(data), dont_standardize)
-    data_std <- cbind(data[, remaining_columns, drop = FALSE], data_std)
+    remaining_columns <- intersect(colnames(model_data), dont_standardize)
+    data_std <- cbind(model_data[, remaining_columns, drop = FALSE], data_std)
   }