对 R 编程中的一个因素进行分析——factanal()函数

因子分析也称为探索性因子分析，是 R 编程中使用的一种统计技术，用于识别不活跃的关系结构，并进一步将变量池缩小到少数变量。使用这种技术的主要动机是找出哪个因素对权重分类的影响最大。

Syntax: factanal(x, factors)

Parameters:
x: represents dataset
factors: specifies number of factors to be fitted

例子：
让我们假设，数据集中有许多可用的食物及其食物质地数据点，例如油、密度、脆皮、断裂和硬度。

# Reading csv file of food textures
food_textures <- read.csv("https://userpage.fu-berlin.de/soga/300/30100_data_sets/food-texture.csv")
  
food_textures <- food_textures[, 2:6]
  
factor_analysis <- factanal(food_textures, factors = 2)
  
print(factor_analysis)
  
# Output to be present as PNG file 
png(file = "factorAnalysisGFG.png")
  
# Plot factor 1 by factor 2
load <- factor_analysis$loadings[, 1:2]
  
# Plot graph
plot(load, type = "n")
text(load, labels = names(food_textures), cex = .9)
  
# Saving the file
dev.off()

输出：

Call:
factanal(x = food_textures, factors = 2)

Uniquenesses:
     Oil  Density   Crispy Fracture Hardness 
   0.334    0.156    0.042    0.256    0.407 

Loadings:
         Factor1 Factor2
Oil      -0.816         
Density   0.919         
Crispy   -0.745   0.635 
Fracture  0.645  -0.573 
Hardness          0.764 

               Factor1 Factor2
SS loadings      2.490   1.316
Proportion Var   0.498   0.263
Cumulative Var   0.498   0.761

Test of the hypothesis that 2 factors are sufficient.
The chi-square statistic is 0.27 on 1 degree of freedom.
The p-value is 0.603