diff --git a/R-package/R/lgb.Booster.R b/R-package/R/lgb.Booster.R
index fa34c182b64e..d53bb6ba97f8 100644
--- a/R-package/R/lgb.Booster.R
+++ b/R-package/R/lgb.Booster.R
@@ -743,15 +743,18 @@ Booster <- R6::R6Class(
 #' data(agaricus.test, package = "lightgbm")
 #' test <- agaricus.test
 #' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
-#' params <- list(objective = "regression", metric = "l2")
+#' params <- list(
+#'   objective = "regression"
+#'   , metric = "l2"
+#'   , min_data = 1L
+#'   , learning_rate = 1.0
+#' )
 #' valids <- list(test = dtest)
 #' model <- lgb.train(
 #'   params = params
 #'   , data = dtrain
 #'   , nrounds = 5L
 #'   , valids = valids
-#'   , min_data = 1L
-#'   , learning_rate = 1.0
 #' )
 #' preds <- predict(model, test$data)
 #'
@@ -824,15 +827,18 @@ predict.lgb.Booster <- function(object,
 #' data(agaricus.test, package = "lightgbm")
 #' test <- agaricus.test
 #' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
-#' params <- list(objective = "regression", metric = "l2")
+#' params <- list(
+#'   objective = "regression"
+#'   , metric = "l2"
+#'   , min_data = 1L
+#'   , learning_rate = 1.0
+#' )
 #' valids <- list(test = dtest)
 #' model <- lgb.train(
 #'   params = params
 #'   , data = dtrain
 #'   , nrounds = 5L
 #'   , valids = valids
-#'   , min_data = 1L
-#'   , learning_rate = 1.0
 #'   , early_stopping_rounds = 3L
 #' )
 #' model_file <- tempfile(fileext = ".txt")
@@ -885,15 +891,18 @@ lgb.load <- function(filename = NULL, model_str = NULL) {
 #' data(agaricus.test, package = "lightgbm")
 #' test <- agaricus.test
 #' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
-#' params <- list(objective = "regression", metric = "l2")
+#' params <- list(
+#'   objective = "regression"
+#'   , metric = "l2"
+#'   , min_data = 1L
+#'   , learning_rate = 1.0
+#' )
 #' valids <- list(test = dtest)
 #' model <- lgb.train(
 #'   params = params
 #'   , data = dtrain
 #'   , nrounds = 10L
 #'   , valids = valids
-#'   , min_data = 1L
-#'   , learning_rate = 1.0
 #'   , early_stopping_rounds = 5L
 #' )
 #' lgb.save(model, tempfile(fileext = ".txt"))
@@ -936,15 +945,18 @@ lgb.save <- function(booster, filename, num_iteration = NULL) {
 #' data(agaricus.test, package = "lightgbm")
 #' test <- agaricus.test
 #' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
-#' params <- list(objective = "regression", metric = "l2")
+#' params <- list(
+#'   objective = "regression"
+#'   , metric = "l2"
+#'   , min_data = 1L
+#'   , learning_rate = 1.0
+#' )
 #' valids <- list(test = dtest)
 #' model <- lgb.train(
 #'   params = params
 #'   , data = dtrain
 #'   , nrounds = 10L
 #'   , valids = valids
-#'   , min_data = 1L
-#'   , learning_rate = 1.0
 #'   , early_stopping_rounds = 5L
 #' )
 #' json_model <- lgb.dump(model)
@@ -983,15 +995,18 @@ lgb.dump <- function(booster, num_iteration = NULL) {
 #' data(agaricus.test, package = "lightgbm")
 #' test <- agaricus.test
 #' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
-#' params <- list(objective = "regression", metric = "l2")
+#' params <- list(
+#'   objective = "regression"
+#'   , metric = "l2"
+#'   , min_data = 1L
+#'   , learning_rate = 1.0
+#' )
 #' valids <- list(test = dtest)
 #' model <- lgb.train(
 #'   params = params
 #'   , data = dtrain
 #'   , nrounds = 5L
 #'   , valids = valids
-#'   , min_data = 1L
-#'   , learning_rate = 1.0
 #' )
 #'
 #' # Examine valid data_name values
diff --git a/R-package/R/lgb.cv.R b/R-package/R/lgb.cv.R
index c011935080bc..81890a6a90c7 100644
--- a/R-package/R/lgb.cv.R
+++ b/R-package/R/lgb.cv.R
@@ -63,14 +63,17 @@ CVBooster <- R6::R6Class(
 #' data(agaricus.train, package = "lightgbm")
 #' train <- agaricus.train
 #' dtrain <- lgb.Dataset(train$data, label = train$label)
-#' params <- list(objective = "regression", metric = "l2")
+#' params <- list(
+#'   objective = "regression"
+#'   , metric = "l2"
+#'   , min_data = 1L
+#'   , learning_rate = 1.0
+#' )
 #' model <- lgb.cv(
 #'   params = params
 #'   , data = dtrain
 #'   , nrounds = 5L
 #'   , nfold = 3L
-#'   , min_data = 1L
-#'   , learning_rate = 1.0
 #' )
 #' }
 #' @importFrom data.table data.table setorderv
diff --git a/R-package/R/lgb.train.R b/R-package/R/lgb.train.R
index 4d975687967d..6f602fe416a4 100644
--- a/R-package/R/lgb.train.R
+++ b/R-package/R/lgb.train.R
@@ -36,15 +36,18 @@
 #' data(agaricus.test, package = "lightgbm")
 #' test <- agaricus.test
 #' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
-#' params <- list(objective = "regression", metric = "l2")
+#' params <- list(
+#'   objective = "regression"
+#'   , metric = "l2"
+#'   , min_data = 1L
+#'   , learning_rate = 1.0
+#' )
 #' valids <- list(test = dtest)
 #' model <- lgb.train(
 #'   params = params
 #'   , data = dtrain
 #'   , nrounds = 5L
 #'   , valids = valids
-#'   , min_data = 1L
-#'   , learning_rate = 1.0
 #'   , early_stopping_rounds = 3L
 #' )
 #' }
diff --git a/R-package/R/lgb.unloader.R b/R-package/R/lgb.unloader.R
index a24f622cf787..443a0d1899e0 100644
--- a/R-package/R/lgb.unloader.R
+++ b/R-package/R/lgb.unloader.R
@@ -21,15 +21,18 @@
 #' data(agaricus.test, package = "lightgbm")
 #' test <- agaricus.test
 #' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
-#' params <- list(objective = "regression", metric = "l2")
+#' params <- list(
+#'   objective = "regression"
+#'   , metric = "l2"
+#'   , min_data = 1L
+#'   , learning_rate = 1.0
+#' )
 #' valids <- list(test = dtest)
 #' model <- lgb.train(
 #'   params = params
 #'   , data = dtrain
 #'   , nrounds = 5L
 #'   , valids = valids
-#'   , min_data = 1L
-#'   , learning_rate = 1.0
 #' )
 #'
 #' lgb.unloader(restore = FALSE, wipe = FALSE, envir = .GlobalEnv)
diff --git a/R-package/R/readRDS.lgb.Booster.R b/R-package/R/readRDS.lgb.Booster.R
index df48d4807f2d..4844abeb3aa9 100644
--- a/R-package/R/readRDS.lgb.Booster.R
+++ b/R-package/R/readRDS.lgb.Booster.R
@@ -15,15 +15,18 @@
 #' data(agaricus.test, package = "lightgbm")
 #' test <- agaricus.test
 #' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
-#' params <- list(objective = "regression", metric = "l2")
+#' params <- list(
+#'   objective = "regression"
+#'   , metric = "l2"
+#'   , min_data = 1L
+#'   , learning_rate = 1.0
+#' )
 #' valids <- list(test = dtest)
 #' model <- lgb.train(
 #'   params = params
 #'   , data = dtrain
 #'   , nrounds = 10L
 #'   , valids = valids
-#'   , min_data = 1L
-#'   , learning_rate = 1.0
 #'   , early_stopping_rounds = 5L
 #' )
 #' model_file <- tempfile(fileext = ".rds")
diff --git a/R-package/R/saveRDS.lgb.Booster.R b/R-package/R/saveRDS.lgb.Booster.R
index 64b1f78ecc03..705cc266fcbb 100644
--- a/R-package/R/saveRDS.lgb.Booster.R
+++ b/R-package/R/saveRDS.lgb.Booster.R
@@ -26,15 +26,18 @@
 #' data(agaricus.test, package = "lightgbm")
 #' test <- agaricus.test
 #' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
-#' params <- list(objective = "regression", metric = "l2")
+#' params <- list(
+#'   objective = "regression"
+#'   , metric = "l2"
+#'   , min_data = 1L
+#'   , learning_rate = 1.0
+#' )
 #' valids <- list(test = dtest)
 #' model <- lgb.train(
 #'     params = params
 #'     , data = dtrain
 #'     , nrounds = 10L
 #'     , valids = valids
-#'     , min_data = 1L
-#'     , learning_rate = 1.0
 #'     , early_stopping_rounds = 5L
 #' )
 #' model_file <- tempfile(fileext = ".rds")
diff --git a/R-package/man/lgb.cv.Rd b/R-package/man/lgb.cv.Rd
index bec7d9ca4f50..bd098a81dbdc 100644
--- a/R-package/man/lgb.cv.Rd
+++ b/R-package/man/lgb.cv.Rd
@@ -159,14 +159,17 @@ Cross validation logic used by LightGBM
 data(agaricus.train, package = "lightgbm")
 train <- agaricus.train
 dtrain <- lgb.Dataset(train$data, label = train$label)
-params <- list(objective = "regression", metric = "l2")
+params <- list(
+  objective = "regression"
+  , metric = "l2"
+  , min_data = 1L
+  , learning_rate = 1.0
+)
 model <- lgb.cv(
   params = params
   , data = dtrain
   , nrounds = 5L
   , nfold = 3L
-  , min_data = 1L
-  , learning_rate = 1.0
 )
 }
 }
diff --git a/R-package/man/lgb.dump.Rd b/R-package/man/lgb.dump.Rd
index 6fbc5cbe9b43..c9b242a812e3 100644
--- a/R-package/man/lgb.dump.Rd
+++ b/R-package/man/lgb.dump.Rd
@@ -26,15 +26,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label)
 data(agaricus.test, package = "lightgbm")
 test <- agaricus.test
 dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
-params <- list(objective = "regression", metric = "l2")
+params <- list(
+  objective = "regression"
+  , metric = "l2"
+  , min_data = 1L
+  , learning_rate = 1.0
+)
 valids <- list(test = dtest)
 model <- lgb.train(
   params = params
   , data = dtrain
   , nrounds = 10L
   , valids = valids
-  , min_data = 1L
-  , learning_rate = 1.0
   , early_stopping_rounds = 5L
 )
 json_model <- lgb.dump(model)
diff --git a/R-package/man/lgb.get.eval.result.Rd b/R-package/man/lgb.get.eval.result.Rd
index 917e0a403a18..cb54217bc42d 100644
--- a/R-package/man/lgb.get.eval.result.Rd
+++ b/R-package/man/lgb.get.eval.result.Rd
@@ -40,15 +40,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label)
 data(agaricus.test, package = "lightgbm")
 test <- agaricus.test
 dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
-params <- list(objective = "regression", metric = "l2")
+params <- list(
+  objective = "regression"
+  , metric = "l2"
+  , min_data = 1L
+  , learning_rate = 1.0
+)
 valids <- list(test = dtest)
 model <- lgb.train(
   params = params
   , data = dtrain
   , nrounds = 5L
   , valids = valids
-  , min_data = 1L
-  , learning_rate = 1.0
 )
 
 # Examine valid data_name values
diff --git a/R-package/man/lgb.load.Rd b/R-package/man/lgb.load.Rd
index 4cdbf79fa988..55d241b2d670 100644
--- a/R-package/man/lgb.load.Rd
+++ b/R-package/man/lgb.load.Rd
@@ -26,15 +26,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label)
 data(agaricus.test, package = "lightgbm")
 test <- agaricus.test
 dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
-params <- list(objective = "regression", metric = "l2")
+params <- list(
+  objective = "regression"
+  , metric = "l2"
+  , min_data = 1L
+  , learning_rate = 1.0
+)
 valids <- list(test = dtest)
 model <- lgb.train(
   params = params
   , data = dtrain
   , nrounds = 5L
   , valids = valids
-  , min_data = 1L
-  , learning_rate = 1.0
   , early_stopping_rounds = 3L
 )
 model_file <- tempfile(fileext = ".txt")
diff --git a/R-package/man/lgb.save.Rd b/R-package/man/lgb.save.Rd
index 9ac19eadb3fc..0736c26ab3f6 100644
--- a/R-package/man/lgb.save.Rd
+++ b/R-package/man/lgb.save.Rd
@@ -28,15 +28,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label)
 data(agaricus.test, package = "lightgbm")
 test <- agaricus.test
 dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
-params <- list(objective = "regression", metric = "l2")
+params <- list(
+  objective = "regression"
+  , metric = "l2"
+  , min_data = 1L
+  , learning_rate = 1.0
+)
 valids <- list(test = dtest)
 model <- lgb.train(
   params = params
   , data = dtrain
   , nrounds = 10L
   , valids = valids
-  , min_data = 1L
-  , learning_rate = 1.0
   , early_stopping_rounds = 5L
 )
 lgb.save(model, tempfile(fileext = ".txt"))
diff --git a/R-package/man/lgb.train.Rd b/R-package/man/lgb.train.Rd
index 80a3ba84f101..4c8935df4f2d 100644
--- a/R-package/man/lgb.train.Rd
+++ b/R-package/man/lgb.train.Rd
@@ -144,15 +144,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label)
 data(agaricus.test, package = "lightgbm")
 test <- agaricus.test
 dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
-params <- list(objective = "regression", metric = "l2")
+params <- list(
+  objective = "regression"
+  , metric = "l2"
+  , min_data = 1L
+  , learning_rate = 1.0
+)
 valids <- list(test = dtest)
 model <- lgb.train(
   params = params
   , data = dtrain
   , nrounds = 5L
   , valids = valids
-  , min_data = 1L
-  , learning_rate = 1.0
   , early_stopping_rounds = 3L
 )
 }
diff --git a/R-package/man/lgb.unloader.Rd b/R-package/man/lgb.unloader.Rd
index d3a0bbd01f74..5a07d3eb1e17 100644
--- a/R-package/man/lgb.unloader.Rd
+++ b/R-package/man/lgb.unloader.Rd
@@ -33,15 +33,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label)
 data(agaricus.test, package = "lightgbm")
 test <- agaricus.test
 dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
-params <- list(objective = "regression", metric = "l2")
+params <- list(
+  objective = "regression"
+  , metric = "l2"
+  , min_data = 1L
+  , learning_rate = 1.0
+)
 valids <- list(test = dtest)
 model <- lgb.train(
   params = params
   , data = dtrain
   , nrounds = 5L
   , valids = valids
-  , min_data = 1L
-  , learning_rate = 1.0
 )
 
 lgb.unloader(restore = FALSE, wipe = FALSE, envir = .GlobalEnv)
diff --git a/R-package/man/predict.lgb.Booster.Rd b/R-package/man/predict.lgb.Booster.Rd
index d80515e99552..313d2dc7eb63 100644
--- a/R-package/man/predict.lgb.Booster.Rd
+++ b/R-package/man/predict.lgb.Booster.Rd
@@ -74,15 +74,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label)
 data(agaricus.test, package = "lightgbm")
 test <- agaricus.test
 dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
-params <- list(objective = "regression", metric = "l2")
+params <- list(
+  objective = "regression"
+  , metric = "l2"
+  , min_data = 1L
+  , learning_rate = 1.0
+)
 valids <- list(test = dtest)
 model <- lgb.train(
   params = params
   , data = dtrain
   , nrounds = 5L
   , valids = valids
-  , min_data = 1L
-  , learning_rate = 1.0
 )
 preds <- predict(model, test$data)
 
diff --git a/R-package/man/readRDS.lgb.Booster.Rd b/R-package/man/readRDS.lgb.Booster.Rd
index add489441986..3592148ac128 100644
--- a/R-package/man/readRDS.lgb.Booster.Rd
+++ b/R-package/man/readRDS.lgb.Booster.Rd
@@ -26,15 +26,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label)
 data(agaricus.test, package = "lightgbm")
 test <- agaricus.test
 dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
-params <- list(objective = "regression", metric = "l2")
+params <- list(
+  objective = "regression"
+  , metric = "l2"
+  , min_data = 1L
+  , learning_rate = 1.0
+)
 valids <- list(test = dtest)
 model <- lgb.train(
   params = params
   , data = dtrain
   , nrounds = 10L
   , valids = valids
-  , min_data = 1L
-  , learning_rate = 1.0
   , early_stopping_rounds = 5L
 )
 model_file <- tempfile(fileext = ".rds")
diff --git a/R-package/man/saveRDS.lgb.Booster.Rd b/R-package/man/saveRDS.lgb.Booster.Rd
index 76f1165f851b..02f5a715762c 100644
--- a/R-package/man/saveRDS.lgb.Booster.Rd
+++ b/R-package/man/saveRDS.lgb.Booster.Rd
@@ -50,15 +50,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label)
 data(agaricus.test, package = "lightgbm")
 test <- agaricus.test
 dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
-params <- list(objective = "regression", metric = "l2")
+params <- list(
+  objective = "regression"
+  , metric = "l2"
+  , min_data = 1L
+  , learning_rate = 1.0
+)
 valids <- list(test = dtest)
 model <- lgb.train(
     params = params
     , data = dtrain
     , nrounds = 10L
     , valids = valids
-    , min_data = 1L
-    , learning_rate = 1.0
     , early_stopping_rounds = 5L
 )
 model_file <- tempfile(fileext = ".rds")