R语言进行主成分分析

导入数据

csvpath <- file.choose()
csvpath

读取数据

data <- read.csv(csvpath, header = T, rows.names = 1)

如下图示例所示：

图片 1.png

调用主成分分析函数princomp

df.pr <- princomp(data, cor = T)

summary(df.pr, loadings = T)
> summary(df.pr, loadings = T)
Importance of components:
                          Comp.1    Comp.2    Comp.3     Comp.4
Standard deviation     2.0513375 0.7302803 0.3937626 0.31643891
Proportion of Variance 0.8415971 0.1066619 0.0310098 0.02002672
Cumulative Proportion  0.8415971 0.9482589 0.9792687 0.99929545
                             Comp.5
Standard deviation     0.0593527515
Proportion of Variance 0.0007045498
Cumulative Proportion  1.0000000000

Loadings:
       Comp.1 Comp.2 Comp.3 Comp.4 Comp.5
height  0.467         0.231  0.850       
DBH     0.366 -0.897  0.166 -0.184       
Length  0.458        -0.875         0.156
lantdh  0.463  0.334  0.372 -0.416  0.603
square  0.474  0.283  0.125 -0.265 -0.781
#Cumulative Proportion 表示各个变量的累积贡献率

绘制碎石图

screeplot(df.pr,type = "lines")

image.png