remove redundant comment

R/check_autocorrelation.R

@@ -29,7 +29,6 @@ check_autocorrelation <- function(x, ...) {
 #' @rdname check_autocorrelation
 #' @export
 check_autocorrelation.default <- function(x, nsim = 1000, ...) {
-  # check for valid input
   .is_model_valid(x)
 
   .residuals <- stats::residuals(x)

R/check_collinearity.R

@@ -145,7 +145,6 @@ multicollinearity <- check_collinearity
 #' @rdname check_collinearity
 #' @export
 check_collinearity.default <- function(x, ci = 0.95, verbose = TRUE, ...) {
-  # check for valid input
   .is_model_valid(x)
   .check_collinearity(x, component = "conditional", ci = ci, verbose = verbose)
 }

R/check_convergence.R

@@ -76,7 +76,6 @@ check_convergence <- function(x, tolerance = 0.001, ...) {
 
 #' @export
 check_convergence.default <- function(x, tolerance = 0.001, ...) {
-  # check for valid input
   .is_model_valid(x)
   message(sprintf("`check_convergence()` does not work for models of class '%s'.", class(x)[1]))
 }

R/check_distribution.R

@@ -66,7 +66,6 @@ check_distribution <- function(model) {
 
 #' @export
 check_distribution.default <- function(model) {
-  # check for valid input
   .is_model_valid(model)
 
   insight::check_if_installed("randomForest")

R/check_heteroscedasticity.R

@@ -46,7 +46,6 @@ check_heteroskedasticity <- check_heteroscedasticity
 
 #' @export
 check_heteroscedasticity.default <- function(x, ...) {
-  # check for valid input
   .is_model_valid(x)
 
   # only for linear models

R/check_itemscale.R

@@ -66,7 +66,6 @@
 #' )
 #' @export
 check_itemscale <- function(x, factor_index = NULL) {
-  # check for valid input
   if (!inherits(x, c("parameters_pca", "data.frame"))) {
     insight::format_error(
       "`x` must be an object of class `parameters_pca`, as returned by `parameters::principal_components()`, or a data frame." # nolint

R/check_normality.R

@@ -55,7 +55,6 @@ check_normality <- function(x, ...) {
 
 #' @export
 check_normality.default <- function(x, ...) {
-  # check for valid input
   .is_model_valid(x)
 
   if (!insight::model_info(x)$is_linear) {

R/check_overdispersion.R

@@ -77,7 +77,6 @@ check_overdispersion <- function(x, ...) {
 
 #' @export
 check_overdispersion.default <- function(x, ...) {
-  # check for valid input
   .is_model_valid(x)
   insight::format_error(
     paste0("`check_overdisperion()` not yet implemented for models of class `", class(x)[1], "`.")

R/check_predictions.R

@@ -100,7 +100,6 @@ check_predictions.default <- function(object,
                                       type = "density",
                                       verbose = TRUE,
                                       ...) {
-  # check for valid input
   .is_model_valid(object)
 
   # retrieve model information

R/model_performance.bayesian.R

@@ -79,7 +79,7 @@ model_performance.stanreg <- function(model, metrics = "all", verbose = TRUE, ..
     metrics <- c("LOOIC", "WAIC", "R2", "RMSE")
   }
 
-  # check for valid input
+
   metrics <- toupper(.check_bad_metrics(metrics, all_metrics, verbose))
 
   algorithm <- insight::find_algorithm(model)
@@ -232,7 +232,7 @@ model_performance.BFBayesFactor <- function(model,
     metrics <- all_metrics
   }
 
-  # check for valid input
+
   metrics <- toupper(.check_bad_metrics(metrics, all_metrics, verbose))
 
   # check for valid BFBayesFactor object

R/model_performance.bife.R

@@ -11,7 +11,7 @@ model_performance.bife <- function(model, metrics = "all", verbose = TRUE, ...)
     metrics <- c("AIC", "R2")
   }
 
-  # check for valid input
+
   metrics <- .check_bad_metrics(metrics, all_metrics, verbose)
 
   info <- insight::model_info(model)

R/model_performance.ivreg.R

@@ -24,7 +24,7 @@ model_performance.ivreg <- function(model, metrics = "all", verbose = TRUE, ...)
     metrics <- c("AIC", "BIC", "R2", "R2_adj", "RMSE")
   }
 
-  # check for valid input
+
   metrics <- .check_bad_metrics(metrics, all_metrics, verbose)
 
   # the lm-method does not accept ivreg-specific metrics

R/model_performance.lm.R

@@ -58,7 +58,7 @@ model_performance.lm <- function(model, metrics = "all", verbose = TRUE, ...) {
     insight::formula_ok(model)
   }
 
-  # check for valid input
+
   metrics <- .check_bad_metrics(metrics, all_metrics, verbose)
   info <- suppressWarnings(insight::model_info(model, verbose = FALSE))
 

R/model_performance.mixed.R

@@ -57,7 +57,7 @@ model_performance.merMod <- function(model,
     metrics <- c("AIC", "BIC", "R2", "ICC", "RMSE")
   }
 
-  # check for valid input
+
   metrics <- .check_bad_metrics(metrics, all_metrics, verbose)
 
   # check model formula

R/model_performance_default.R

@@ -1,6 +1,5 @@
 #' @export
 model_performance.default <- function(model, metrics = "all", verbose = TRUE, ...) {
-  # check for valid input
   .is_model_valid(model)
 
   if (any(tolower(metrics) == "log_loss")) {
@@ -16,7 +15,7 @@ model_performance.default <- function(model, metrics = "all", verbose = TRUE, ..
     metrics <- c("AIC", "BIC", "R2", "R2_adj", "RMSE")
   }
 
-  # check for valid input
+
   metrics <- .check_bad_metrics(metrics, all_metrics, verbose)
 
   if (!insight::is_model(model) || !insight::is_model_supported(model)) {
@@ -32,7 +31,6 @@ model_performance.default <- function(model, metrics = "all", verbose = TRUE, ..
 
 
 .check_bad_metrics <- function(metrics, all_metrics, verbose = TRUE) {
-  # check for valid input
   bad_metrics <- which(!metrics %in% all_metrics)
   if (length(bad_metrics)) {
     if (verbose) {

R/performance_aicc.R

@@ -69,7 +69,6 @@ performance_aic <- function(x, ...) {
 #' @rdname performance_aicc
 #' @export
 performance_aic.default <- function(x, estimator = "ML", verbose = TRUE, ...) {
-  # check for valid input
   .is_model_valid(x)
 
   info <- list(...)$model_info
@@ -203,7 +202,6 @@ AIC.bife <- function(object, ..., k = 2) {
 
 #' @export
 performance_aicc.default <- function(x, estimator = "ML", ...) {
-  # check for valid input
   .is_model_valid(x)
 
   # check ML estimator

R/performance_logloss.R

@@ -30,7 +30,6 @@ performance_logloss <- function(model, verbose = TRUE, ...) {
 
 #' @export
 performance_logloss.default <- function(model, verbose = TRUE, ...) {
-  # check for valid input
   .is_model_valid(model)
 
   resp <- .recode_to_zero(insight::get_response(model, verbose = verbose))

R/performance_mae.R

@@ -25,7 +25,6 @@ mae <- performance_mae
 
 #' @export
 performance_mae.default <- function(model, verbose = TRUE, ...) {
-  # check for valid input
   .is_model_valid(model)
 
   pred <- .safe(insight::get_predicted(model, ci = NULL, verbose = verbose, ...))