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R中的矢量化仿真

[英]vectorized simulation in R

I've written a simulation function in R . 我已经在R中编写了一个仿真函数。 I'd like to do num simulations. 我想进行num模拟。 Rather than using a for loop, I'm trying to use some sort of apply function, such as lapply or parallel::mclapply . 我尝试使用某种应用功能,而不是使用for循环,例如lapplyparallel::mclapply

lapply , as I'm currently using it, is failing. 我目前正在使用的lapply失败了。

For example: 例如:

# t1() is a generic example function
t1 <- function() {data(cars); return(get("cars"))}
a <- t1() # works
a2 <- vector("list", 5) # pre-allocate list for 5 simulations
# otherwise: a2 <- vector("list", num) # where num was pre-specified
a2 <- lapply(a2, t1) 
## Error in FUN(X[[1L]], ...) : unused argument (X[[1]])

What am I doing wrong? 我究竟做错了什么? Thanks in advance! 提前致谢!

I'd rather not need to do: 我宁愿不需要做:

a2 <- vector("list", 5)
for (i in 1:5) {
  a2[[i]] <- t1()
}

It's true that a <- t1() works but it's not true that a <- t1(2) would have "worked". 这是真的, a <- t1()的作品,但它不是真的, a <- t1(2)将有“工作”。 You are trying to pass arguments to parameters that are not there. 您正在尝试将参数传递给不存在的参数。 Put a dummy parameter in the argument list and all will be fine. 将一个虚拟参数放在参数列表中,一切都会好的。 You might also look at the replicate function. 您可能还会查看replicate功能。 It is specifically designed to support simulation efforts. 它是专门为支持仿真工作而设计的。 I think you will find that it does not require including dummy parameters in the argument list. 我认为您会发现它不需要在参数列表中包含虚拟参数。

> t1 <- function(z) {data(cars); return(get("cars"))}
> a <- t1() # works
> a2 <- vector("list", 5) # pre-allocate list for 5 simulations
> # otherwise: a2 <- vector("list", num) # where num was pre-specified
> a2 <- lapply(a2, t1) ;str(a2)
List of 5
 $ :'data.frame':   50 obs. of  2 variables:
  ..$ speed: num [1:50] 4 4 7 7 8 9 10 10 10 11 ...
  ..$ dist : num [1:50] 2 10 4 22 16 10 18 26 34 17 ...
 $ :'data.frame':   50 obs. of  2 variables:
  ..$ speed: num [1:50] 4 4 7 7 8 9 10 10 10 11 ...
  ..$ dist : num [1:50] 2 10 4 22 16 10 18 26 34 17 ...
 $ :'data.frame':   50 obs. of  2 variables:
  ..$ speed: num [1:50] 4 4 7 7 8 9 10 10 10 11 ...
  ..$ dist : num [1:50] 2 10 4 22 16 10 18 26 34 17 ...
 $ :'data.frame':   50 obs. of  2 variables:
  ..$ speed: num [1:50] 4 4 7 7 8 9 10 10 10 11 ...
  ..$ dist : num [1:50] 2 10 4 22 16 10 18 26 34 17 ...
 $ :'data.frame':   50 obs. of  2 variables:
  ..$ speed: num [1:50] 4 4 7 7 8 9 10 10 10 11 ...
  ..$ dist : num [1:50] 2 10 4 22 16 10 18 26 34 17 ...
> 

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