如何在R中循环列表的子集？

Question

我有一个9个列表的列表，请参见以下代码，在这里我只想循环三个列表p ， r和t用于Pearson，Spearson和Kendall相关，而不是全部9个列表。 当前伪代码如下，其中测试函数为corrplot(M.cor, ...) ，请参见下面的完整伪代码

for (i in p.mat.all) {
...
}

使用mtcars测试数据进行编码

library("psych")
library("corrplot")   

M <- mtcars 

M.cor <- cor(M)

p.mat.all <- psych::corr.test(M.cor, method = c("pearson", "kendall", "spearman"), 
   adjust = "none", ci = F)

str(p.mat.all)

str(p.mat.all$r)

str(p.mat.all$t)

str(p.mat.all$p)

输出有关9个列表的列表

List of 9
 $ r     : num [1:11, 1:11] 1 -0.991 -0.993 -0.956 0.939 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:11] "mpg" "cyl" "disp" "hp" ...
  .. ..$ : chr [1:11] "mpg" "cyl" "disp" "hp" ...
 $ n     : num 11
 $ t     : num [1:11, 1:11] Inf -21.92 -25.4 -9.78 8.22 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:11] "mpg" "cyl" "disp" "hp" ...
  .. ..$ : chr [1:11] "mpg" "cyl" "disp" "hp" ...
 $ p     : num [1:11, 1:11] 0.00 4.04e-09 1.09e-09 4.32e-06 1.78e-05 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:11] "mpg" "cyl" "disp" "hp" ...
  .. ..$ : chr [1:11] "mpg" "cyl" "disp" "hp" ...
 $ se    : num [1:11, 1:11] 0 0.0452 0.0391 0.0978 0.1143 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:11] "mpg" "cyl" "disp" "hp" ...
  .. ..$ : chr [1:11] "mpg" "cyl" "disp" "hp" ...
 $ adjust: chr "none"
 $ sym   : logi TRUE
 $ ci    : NULL
 $ Call  : language psych::corr.test(x = M.cor, method = c("pearson", "kendall", "spearman"),      adjust = "none", ci = F)
 - attr(*, "class")= chr [1:2] "psych" "corr.test"
 num [1:11, 1:11] 1 -0.991 -0.993 -0.956 0.939 ...
 - attr(*, "dimnames")=List of 2
  ..$ : chr [1:11] "mpg" "cyl" "disp" "hp" ...
  ..$ : chr [1:11] "mpg" "cyl" "disp" "hp" ...
 num [1:11, 1:11] Inf -21.92 -25.4 -9.78 8.22 ...
 - attr(*, "dimnames")=List of 2
  ..$ : chr [1:11] "mpg" "cyl" "disp" "hp" ...
  ..$ : chr [1:11] "mpg" "cyl" "disp" "hp" ...
 num [1:11, 1:11] 0.00 4.04e-09 1.09e-09 4.32e-06 1.78e-05 ...
 - attr(*, "dimnames")=List of 2
  ..$ : chr [1:11] "mpg" "cyl" "disp" "hp" ...
  ..$ : chr [1:11] "mpg" "cyl" "disp" "hp" ...

我关于用测试函数corrplot循环所有三个相关性的伪代码，但由于它遍历了所有9个列表，因此无法正常工作

for (i in p.mat.all) {
  p.mat <- i
  print("p.mat ===========")
  print(i)    

  alpha <- 0.05 
  corrplot( M.cor,  
          method="color", 
          type="upper", 
          addCoefasPercent = TRUE, 
          tl.col = "black",
          tl.pos = "td", 
          p.mat = p.mat, sig.level = alpha, insig = "blank", 
          order = "original"
  )
}

预期的输出：仅循环t ， p和r列表，以便可以将它们传递到测试函数corrplot

R：3.3.1
操作系统：Debian 8.5

Answer 1

或带有* apply函数：

lapply(p.mat.all[c("r","p","t")], function(x) {
  # x takes now first p.mat.all$r, then p.mat.all$p, etc
  print("p.mat ===========")
  print(x)    

  alpha <- 0.05 
  corrplot( M.cor,  
          method="color", 
          type="upper", 
          addCoefasPercent = TRUE, 
          tl.col = "black",
          tl.pos = "td", 
          p.mat = x, sig.level = alpha, insig = "blank", 
          order = "original"
  )
})

Answer 2

我的建议是在循环之前过滤列表，即

for (i in p.mat.all[c("t", "p", "r")]) { 
    ...
}

r corrplot， t corrplot和p corrplot的输出