Рассмотрим редко используемого члена семейства применения, rapply
(рекурсивный член применения):
rapply(res, print)
Для демонстрации:
set.seed(9222018)
# NESTED LIST OF FIVE LISTS EACH WITH ONE 5 X 2 MATRIX
res <- lapply(1:5, function(x) list(replicate(2, runif(5))))
str(res)
# List of 5
# $ :List of 1
# ..$ : num [1:5, 1:2] 0.233 0.959 0.242 0.131 0.924 ...
# $ :List of 1
# ..$ : num [1:5, 1:2] 0.0347 0.0409 0.9717 0.1854 0.6874 ...
# $ :List of 1
# ..$ : num [1:5, 1:2] 0.579 0.994 0.339 0.554 0.188 ...
# $ :List of 1
# ..$ : num [1:5, 1:2] 0.306 0.828 0.29 0.416 0.57 ...
# $ :List of 1
# ..$ : num [1:5, 1:2] 0.722 0.117 0.292 0.32 0.131 ...
Вывод
out <- rapply(res, print, how="list")
# [,1] [,2]
# [1,] 0.2334018 0.4563486
# [2,] 0.9593926 0.8900761
# [3,] 0.2415238 0.1898711
# [4,] 0.1312646 0.2723704
# [5,] 0.9238483 0.5405712
# [,1] [,2]
# [1,] 0.03469751 0.6921262
# [2,] 0.04085011 0.9977958
# [3,] 0.97173617 0.7002101
# [4,] 0.18537097 0.7687420
# [5,] 0.68738469 0.8482499
# [,1] [,2]
# [1,] 0.5789794 0.53362949
# [2,] 0.9938713 0.06445358
# [3,] 0.3390548 0.56161016
# [4,] 0.5536486 0.69291413
# [5,] 0.1878046 0.34357447
# [,1] [,2]
# [1,] 0.3062696 0.8913562
# [2,] 0.8281726 0.7861409
# [3,] 0.2902253 0.3713141
# [4,] 0.4156087 0.8301594
# [5,] 0.5695427 0.5160663
# [,1] [,2]
# [1,] 0.7217106 0.3459698
# [2,] 0.1174953 0.4014062
# [3,] 0.2917907 0.6519540
# [4,] 0.3204130 0.6228116
# [5,] 0.1309318 0.9475084
И поскольку мы печатаем каждый элемент без их изменения, out точно такой же, как res :
identical(res, out)
# TRUE