r - 在 R 中没有重复组星座的子组中对多个个体进行采样

Question

我有多个individuals我想 - 随机 - 分成大小为 groupsize 的子组.这个过程我要重复一遍n_group次 - 没有重复的群星座。
我怎样才能在 R 中实现这一点？

到目前为止，我尝试了以下方法:

set.seed(1)
individuals <- 1:6
groupsize <- 3
n_groups <- 4

for(i in 1:n_groups) { print(sample(individuals, groupsize))}

[1] 1 4 3
[1] 1 2 6
[1] 3 2 6
[1] 3 1 5

..但我不确定这是否真的不会导致重复星座..？

编辑:在查看我意识到的第一个建议和答案之后，另一个限制对我来说可能很有趣(抱歉没有预先看到它......)。
是否(在上面的具体示例中)有一种方法可以确保每个人都与其他人保持联系？

Answer 1

根据您编辑的问题，我假设您想确保所有个体都至少属于一个子组？
那么这可能是解决方案:

individuals <- 1:6
groupsize <- 3
n_groups <- 4

#sample groups
library(RcppAlgos)
#initialise
answer <- matrix()
# If the length of all unique elements in the answer is smaller than
# the number of individuals, take a new sample
while (length(unique(as.vector(answer))) < length(individuals)) {
  answer <- comboSample(individuals, groupsize, n = n_groups)
  # Line below isfor demonstration only
  #answer <- comboSample(individuals, groupsize, n = n_groups, seed = 123)
}
# sample answer with seed = 123 (see commented line above)
#      [,1] [,2] [,3]
# [1,]    1    3    4
# [2,]    1    3    6
# [3,]    2    3    5
# [4,]    2    3    4

测试不包含每个人的组

# Test with the following matrix
#      [,1] [,2] [,3]
# [1,]    1    2    3
# [2,]    1    3    4
# [3,]    1    4    5
# [4,]    2    3    4
# Note that individual '6' is not present
answer <- matrix(c(1,2,3,1,3,4,1,4,5,2,3,4), nrow = 4, ncol = 3)
while (length(unique(as.vector(answer))) < length(individuals)) {
  answer <- comboSample(individuals, groupsize, n = n_groups)
}
# is recalculated to (in this case) the following answer
#      [,1] [,2] [,3]
# [1,]    4    5    6
# [2,]    3    4    5
# [3,]    1    3    6
# [4,]    2    4    5

通过;-)