performance - Replicate() 与 for 循环？

Question

有谁知道replicate() 函数在R 中是如何工作的，以及它相对于使用for 循环的效率如何？

例如，...之间是否存在效率差异？

means <- replicate(100000, mean(rnorm(50)))

和...

means <- c()
for(i in 1:100000) { 
   means <- c(means, mean(rnorm(50)))
}

(我可能在上面输入了一些内容，但你明白了。)

Answer 1

您可以对代码进行基准测试并凭经验获得答案。请注意，我还添加了第二个 for 循环风格，它通过预分配向量来规避不断增长的向量问题。

repl_function = function(no_rep) means <- replicate(no_rep, mean(rnorm(50)))
for_loop = function(no_rep) {
   means <- c()
   for(i in 1:no_rep) { 
      means <- c(means, mean(rnorm(50)))
   }
   means
}
for_loop_prealloc = function(no_rep) {
   means <- vector(mode = "numeric", length = no_rep)
   for(i in 1:no_rep) { 
      means[i] <- mean(rnorm(50))
   }
   means
}

no_loops = 50e3
benchmark(repl_function(no_loops), 
          for_loop(no_loops), 
          for_loop_prealloc(no_loops), 
          replications = 3)

                         test replications elapsed relative user.self sys.self
2          for_loop(no_loops)            3  18.886    6.274    17.803    0.894                          
3 for_loop_prealloc(no_loops)            3   3.209    1.066     3.189    0.000                          
1     repl_function(no_loops)            3   3.010    1.000     2.997    0.000                          
  user.child sys.child
2          0         0                                                                                  
3          0         0                                                                                  
1          0         0 

看着 relative列，未预分配的 for 循环慢 6.2 倍。但是，预分配的 for 循环与 replicate 一样快.