Carga datos

library(readr)
library(kableExtra)
url_link<-"http://halweb.uc3m.es/esp/Personal/personas/agrane/libro/ficheros_datos/capitulo_7/datos_prob_7_3.txt"
mat_X<-read_table2(url_link,col_names = FALSE)
## Parsed with column specification:
## cols(
##   X1 = col_double(),
##   X2 = col_double(),
##   X3 = col_double(),
##   X4 = col_double(),
##   X5 = col_double(),
##   X6 = col_double(),
##   X7 = col_double(),
##   X8 = col_double()
## )
mat_X %>% head() %>% 
  kable(caption ="Matriz de información:" ,align = "c",digits = 6) %>% 
  kable_material(html_font = "sans-serif")
Matriz de información:
X1 X2 X3 X4 X5 X6 X7 X8
30 41 670 3903 12 94 341 1.2
124 46 410 955 6 57 89 0.5
95 48 370 6 5 26 20 0.1
90 43 680 435 8 20 331 1.6
112 41 100 1293 2 51 22 0.1
73 51 390 6115 4 35 93 0.2

R

library(dplyr)
## 
## Attaching package: 'dplyr'
## The following object is masked from 'package:kableExtra':
## 
##     group_rows
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
library(kableExtra)
cor(mat_X) %>% 
  kable(caption="Cálculo de R(X) a través de R base",
        align = "c",
        digits = 2) %>% 
  kable_material(html_font = "sans-serif") %>% 
  kable_styling(bootstrap_options = c("striped", "hover"))
Cálculo de R(X) a través de R base
X1 X2 X3 X4 X5 X6 X7 X8
X1 1.00 0.25 -0.53 -0.25 -0.63 -0.23 -0.53 -0.36
X2 0.25 1.00 -0.11 0.17 -0.50 -0.84 -0.23 -0.12
X3 -0.53 -0.11 1.00 0.27 0.54 0.03 0.71 0.73
X4 -0.25 0.17 0.27 1.00 0.18 0.02 0.45 0.32
X5 -0.63 -0.50 0.54 0.18 1.00 0.35 0.61 0.42
X6 -0.23 -0.84 0.03 0.02 0.35 1.00 0.15 -0.03
X7 -0.53 -0.23 0.71 0.45 0.61 0.15 1.00 0.93
X8 -0.36 -0.12 0.73 0.32 0.42 -0.03 0.93 1.00

##Usando Paquete corr

library(corrplot)
## corrplot 0.84 loaded
library(grDevices)
library(Hmisc)
## Loading required package: lattice
## Loading required package: survival
## Loading required package: Formula
## Loading required package: ggplot2
## 
## Attaching package: 'Hmisc'
## The following objects are masked from 'package:dplyr':
## 
##     src, summarize
## The following objects are masked from 'package:base':
## 
##     format.pval, units
Mat_R<-rcorr(as.matrix(mat_X))
corrplot(Mat_R$r,
         p.mat = Mat_R$r,
         type="upper",
         tl.col="black",
         tl.srt = 20,
         pch.col = "blue",
         insig = "p-value",
         sig.level = -1,
col = terrain.colors(100))

##EJEMPLO 1

library(corrplot)
library(grDevices)
library(Hmisc)
col2 <- colorRampPalette(c("pink", "orange", "blue")) 
Mat_R<-rcorr(as.matrix(mat_X))
corrplot(Mat_R$r,
         p.mat = Mat_R$r,
         type="full",
         method = "circle",
         tl.col="black",
         tl.srt = 45,
         pch.col = "blue",
         insig = "p-value",
          order="hclust",
         addrect = 2,
         sig.level = -1,
         col = col2(50))

##Ejemplo 2

library(corrplot)
library(grDevices)
library(Hmisc)
col2 <- colorRampPalette(c("red", "green", "yellow")) 
Mat_R<-rcorr(as.matrix(mat_X))
corrplot(Mat_R$r,
         p.mat = Mat_R$r,
         type="full",
         method = "circle",
         tl.col="black",
         tl.srt = 45,
         pch.col = "blue",
         insig = "p-value",
          order="hclust",
         addrect = 2,
         sig.level = -1,
         col = col2(50))

##Ejemplo 3

library(corrplot)
library(grDevices)
library(Hmisc)
col2 <- colorRampPalette(c("blue", "green", "pink")) 
Mat_R<-rcorr(as.matrix(mat_X))
corrplot(Mat_R$r,
         p.mat = Mat_R$r,
         type="full",
         method = "circle",
         tl.col="black",
         tl.srt = 45,
         pch.col = "green",
         insig = "p-value",
          order="hclust",
         addrect = 2,
         sig.level = -1,
         col = col2(50))