Multiple Regression Analysis Notes 1

Central University of Finance and Economics

School of Statistics and Mathematics

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Email:dzdyw@email.cufe.edu.cn

(1)

setwd("C:\\Users\\Mr.Young\\Desktop")
X <- read.csv("1-1.csv", header = T)
attach(X)
XX <- data.frame(X$OXY, X$time, X$age)
plot(XX)

(2)

plot(X[2:8])
pairs(X[2:8])

library("car")
scatterplotMatrix(X[2:8], spread = FALSE,
                  smoother = FALSE)

(3)

X3 <- X[c(1,2,21,22), ]
library(lattice)
parallelplot(~X3[2:8], horizontal.axis = FALSE)

轮廓图编程

outline <- function(x){
  if (is.data.frame(x) == TRUE)
    x <- as.matrix(x)
  m <- nrow(x); n <- ncol(x)
  plot(c(1,n), c(min(x),max(x)), type = "n",
       main = "The outline graph of Data",
       xlab = "Number", ylab = "Value")
  for(i in 1:m){
    lines(x[i,], col=i, lty = i)  
  } 
}

outline(X3[2:8])
legend("topleft", title = "Order Number", 
       legend = c("1","2","21","22"),
       lty = 1:4, col = 1:4)

library(fmsb)
radarchart(X3[2:8],axistype = 2,plty = 3:6,seg = 3,
           maxmin = FALSE,title = "Radar Chart")
legend(x = 1.2, y = 1.2, 
       legend = c("1","2","21","22"),
       lty = 3:6,col = c("black","red","green","blue")) 

(4)

library(andrews)
andrews(X3[2:8], type = 1, ymax = 5, 
        main = "Harmonic Diagram")

library(MSG)
andrews_curve(X3[2:8])

调和曲线图编程

unison <- function(x){
  if (is.data.frame(x) == TRUE)
    x <- as.matrix(x)
  t <- seq(-pi, pi, pi/30)
  m <- nrow(x); n<-ncol(x)
  f <- array(0, c(m,length(t)))
  for(i in 1:m){
    f[i,] <- x[i,1]/sqrt(2)
    for( j in 2:n){
      if (j%%2 == 0)
        f[i,] <- f[i,]+x[i,j]*sin(j/2*t)
      else
        f[i,] <- f[i,]+x[i,j]*cos(j%/%2*t)
    }
  }
  plot(c(-pi,pi), c(min(f), max(f)), type = "n", 
       main = "Harmonic Diagram",
       xlab = "t", ylab = "f(t)")
  for(i in 1:m) lines(t, f[i,] , col = i, lty = i)
}

unison(X3[2:8])
legend("topleft", title = "Order Number", 
       legend = c("1","2","21","22"),
       lty = 1:4, col = 1:4)

脸谱图

library(aplpack)

## Loading required package: tcltk

faces(X3[2:8])

## effect of variables:
##  modified item       Var     
##  "height of face   " "age"   
##  "width of face    " "weight"
##  "structure of face" "time"  
##  "height of mouth  " "spulse"
##  "width of mouth   " "rpulse"
##  "smiling          " "mpulse"
##  "height of eyes   " "OXY"   
##  "width of eyes    " "age"   
##  "height of hair   " "weight"
##  "width of hair   "  "time"  
##  "style of hair   "  "spulse"
##  "height of nose  "  "rpulse"
##  "width of nose   "  "mpulse"
##  "width of ear    "  "OXY"   
##  "height of ear   "  "age"

使用函数faces(X,nrow.plot,ncol.plot,…)

X为数值矩阵，每一列代表一个变量

nrow.plot 和ncol.plot分别为图形显示的行列数

1. 用五官的宽度和高度来描绘数值

2. 人对脸谱高度敏感和强记忆

3. 适合较少样本的情况

library("TeachingDemos")

## 
## Attaching package: 'TeachingDemos'
## 
## The following objects are masked from 'package:aplpack':
## 
##     faces, slider

faces2(X3[2:8])