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我有一个包含 9 个列表的列表，请参见下面的代码，其中我只想循环三个列表p，r并t分别针对 Pearson、Spearson 和 Kendall 相关，而不是所有 9 个列表。当前的伪代码如下，测试函数所在的地方corrplot(M.cor, ...)，完整伪代码见下文

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

带有mtcars测试数据的代码

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)

输出关于 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" ...

我关于循环所有三个相关性与测试函数的伪代码corrplot，但它不起作用，因为它遍历了所有 9 个列表

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"
  )
}

预期输出：仅循环和列表t，以便它们可以传递给测试函数prcorrplot

R：3.3.1
操作系统：Debian 8.5

4

2 回答 2

4

或者使用 *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"
  )
})
于 2016-11-10T15:18:35.540 回答
1

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")]) { 
    ...
}

rcorrplot、tcorrplot 和pcorrplot的输出

在此处输入图像描述

于 2016-11-10T15:14:32.630 回答