From 4127d9dcfe5385e6de1dcfe78204b419414b02e3 Mon Sep 17 00:00:00 2001
From: Daniel <mail@danielluedecke.de>
Date: Mon, 18 Mar 2024 11:31:58 +0100
Subject: [PATCH] lintrs, spelling

---
 R/check_overdispersion.R |  6 +++---
 R/check_predictions.R    |  2 +-
 R/check_residuals.R      |  2 +-
 R/simulate_residuals.R   | 12 ++++++------
 man/check_residuals.Rd   |  2 +-
 5 files changed, 12 insertions(+), 12 deletions(-)

diff --git a/R/check_overdispersion.R b/R/check_overdispersion.R
index db4873c18..0a9cfb595 100644
--- a/R/check_overdispersion.R
+++ b/R/check_overdispersion.R
@@ -303,10 +303,10 @@ check_overdispersion.performance_simres <- function(x, alternative = c("two.side
 
   # check for special arguments - we may pass "object_name" from other methods
   dots <- list(...)
-  if (!is.null(dots$object_name)) {
-    obj_name <- dots$object_name
-  } else {
+  if (is.null(dots$object_name)) {
     obj_name <- insight::safe_deparse_symbol(substitute(x))
+  } else {
+    obj_name <- dots$object_name
   }
 
   # statistics function
diff --git a/R/check_predictions.R b/R/check_predictions.R
index a1df0c28f..69222d7f8 100644
--- a/R/check_predictions.R
+++ b/R/check_predictions.R
@@ -106,7 +106,7 @@ check_predictions.default <- function(object,
   minfo <- insight::model_info(object, verbose = FALSE)
 
   # try to find sensible default for "type" argument
-  suggest_dots <- (minfo$is_bernoulli || minfo$is_count || minfo$is_ordinal || minfo$is_categorical || minfo$is_multinomial)
+  suggest_dots <- (minfo$is_bernoulli || minfo$is_count || minfo$is_ordinal || minfo$is_categorical || minfo$is_multinomial) # nolint
   if (missing(type) && suggest_dots) {
     type <- "discrete_interval"
   }
diff --git a/R/check_residuals.R b/R/check_residuals.R
index 7d7d3df3d..2bb284c88 100644
--- a/R/check_residuals.R
+++ b/R/check_residuals.R
@@ -13,7 +13,7 @@
 #'
 #' @details Uniformity of residuals is checked using a Kolmogorov-Smirnov test.
 #' There is a `plot()` method to visualize the distribution of the residuals.
-#' The test fpr uniformity basically tests to which extent the observed values
+#' The test for uniformity basically tests to which extent the observed values
 #' deviate from the model expectations (i.e. simulated values). In this sense,
 #' the `check_residuals()` function has similar goals like [`check_predictions()`].
 #'
diff --git a/R/simulate_residuals.R b/R/simulate_residuals.R
index 3dbba0b5b..207b660db 100644
--- a/R/simulate_residuals.R
+++ b/R/simulate_residuals.R
@@ -97,15 +97,15 @@ plot.performance_simres <- function(x, ...) {
 
 .simres_statistics <- function(x, statistic_fun, alternative = "two.sided") {
   # summarize the observed and simulated residuals
-  if (!is.null(statistic_fun)) {
-    # either apply a function to observed and simulated residusls,
+  if (is.null(statistic_fun)) {
+    # we pass the values to compute the p-value directly (for "check_outliers()")
+    observed <- x
+    simulated <- statistic_fun
+  } else {
+    # or apply a function to observed and simulated residusls,
     # to calcualte a summary statistic
     observed <- statistic_fun(x$observedResponse)
     simulated <- apply(x$simulatedResponse, 2, statistic_fun)
-  } else {
-    # or we pass the values to compute the p-value directly (for "check_outliers()")
-    observed <- x
-    simulated <- statistic_fun
   }
   # p is simply ratio of simulated zeros to observed zeros
   p <- switch(alternative,
diff --git a/man/check_residuals.Rd b/man/check_residuals.Rd
index 5919e1550..dfb56ff83 100644
--- a/man/check_residuals.Rd
+++ b/man/check_residuals.Rd
@@ -30,7 +30,7 @@ residual spatial and temporal autocorrelation.
 \details{
 Uniformity of residuals is checked using a Kolmogorov-Smirnov test.
 There is a \code{plot()} method to visualize the distribution of the residuals.
-The test fpr uniformity basically tests to which extent the observed values
+The test for uniformity basically tests to which extent the observed values
 deviate from the model expectations (i.e. simulated values). In this sense,
 the \code{check_residuals()} function has similar goals like \code{\link[=check_predictions]{check_predictions()}}.
 }