以 "R" 编程语言显示和报告函数输出

Question

在R编程语言和包pcaPP中我有这个代码：

#  multivariate  data  with  outliers
library(mvtnorm)
library(pcaPP)

x  <-  rbind(rmvnorm(200,  rep(0,  6),  diag(c(5,  rep(1,5)))),
             rmvnorm(  15,  c(0,  rep(20,  5)),  diag(rep(1,  6))))
#  Here  we  calculate  the  principal  components  with  PCAgrid
pc  <-  PCAproj(x)

这里是 PCAproj 函数输出值的文档：

The function returns a list of class '"princomp"', i.e. a list
similar to the output of the function 'princomp'.

    sdev: the (robust) standard deviations of the principal components.

loadings: the matrix of variable loadings (i.e., a matrix whose columns 
          contain the eigen- vectors). This is of class "loadings":
          see loadings for its print method.

  center: the means that were subtracted.

   scale: the scalings applied to each variable.

   n.obs: the number of observations.

  scores: if 'scores = TRUE', the scores of the supplied data on the
          principal components.

    call: the matched call.

如何调用 PCAproj 的其他输出，如 loadings 和 sdev 并在 R-studio 中报告这些输出？

Answer 1

在你的例子中，它都存储在pc中。

如果您处于交互模式，只需键入 pc$sdev 和 pc$loading 即可查看它们包含的内容。

> pc$sdev
  Comp.1   Comp.2
2.425413 1.346727


> pc$loadings

Loadings:
   Comp.1 Comp.2
V1  0.972  0.153
V2 -0.201  0.447
V3        -0.130
V4        -0.211
V5         0.739
V6 -0.109  0.412

               Comp.1 Comp.2
SS loadings     1.000  1.000
Proportion Var  0.167  0.167
Cumulative Var  0.167  0.333

Answer 2

补充一下 Bottoms 先生所说的内容，我发现以下一组函数在深入研究 pc 对象等输出时非常有用 -- names()，str(), 和 summary.

# Set Up
library(mvtnorm)
library(pcaPP)
x  <-  rbind(rmvnorm(200,  rep(0,  6),  diag(c(5,  rep(1,5)))),
             rmvnorm(  15,  c(0,  rep(20,  5)),  diag(rep(1,  6))))
pc  <-  PCAproj(x)

names() returns 数据结构中每个元素顶层名称的向量。

> names(pc)
[1] "loadings" "sdev"     "center"   "scale"    "n.obs"    "scores"   "call"

str() 是结构的缩写。它输出一个易于阅读的 R 数据结构描述。我喜欢将其视为 table 的内容。您会注意到它与您的名单相匹配。

str(pc)
List of 7
 $ loadings: loadings [1:6, 1:2] 0.962 0.1011 0.048 0.2461 0.0152 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:6] "V1" "V2" "V3" "V4" ...
  .. ..$ : chr [1:2] "Comp.1" "Comp.2"
 $ sdev    : Named num [1:2] 2.79 1.39
  ..- attr(*, "names")= chr [1:2] "Comp.1" "Comp.2"
 $ center  : num [1:6] 0.193 0.114 0.093 0.117 0.215 ...
 $ scale   : num [1:6(1d)] 1 1 1 1 1 1
 $ n.obs   : int 215
 $ scores  : num [1:215, 1:2] -0.413 1.707 0.835 2.164 0.495 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:215] "1" "2" "3" "4" ...
  .. ..$ : chr [1:2] "Comp.1" "Comp.2"
 $ call    : language PCAproj(x = x)
 - attr(*, "class")= chr [1:2] "pcaPP" "princomp"

summary() 大多数设计良好的函数都允许您将新对象传递到摘要函数中，它 returns ...让我们称它为 "most obvious and useful" 该函数的输出摘要。

> summary(pc)
Importance of components:
                          Comp.1    Comp.2
Standard deviation     2.7873357 1.3855889
Proportion of Variance 0.8018539 0.1981461
Cumulative Proportion  0.8018539 1.0000000

然后 RStudio 和其他 IDE 具有选项卡自动完成等很酷的功能，因此如果您键入 pc$ 然后按下 tab 键，它将列出上面列出的所有这些名称。然后您可以使用箭头键 select 您想要 select 的元素。

> str(pc$loadings)
 loadings [1:6, 1:2] 0.962 0.1011 0.048 0.2461 0.0152 ...
 - attr(*, "dimnames")=List of 2
  ..$ : chr [1:6] "V1" "V2" "V3" "V4" ...
  ..$ : chr [1:2] "Comp.1" "Comp.2"

以 "R" 编程语言显示和报告函数输出

Show and report function outputs in "R" programming language

r

rstudio