Manually creating a correlation matrix in R-CodePudding

I have a correlation table from a book that I want to import into R.

The ultimate goal is to convert this correlation matrix into a covariance matrix using the cor2cov function. However, in order to do that, I need to read in all these values into a corr.mat data type first. How do I do that? Do I read in the values as a dataframe first? Or as vectors?

Thank you!

CodePudding user response：

The function cov gives back the covariance matrix between x and y (Here I added x2 to show you that you can do that with multiple variables). You can transform your covariance matrix to a correlation matrix with cov2cor(df) Use ?cor to get more details about the function.

library(stats)
x <- seq(1,10,1)
x2 <- seq(1,20,2)
y <- c(0,0,0,0,0,0,1,1,1,1)
df <- data.frame(x,x2,y)

print(cov(df))
           x        x2         y
x   9.166667 18.333333 1.3333333
x2 18.333333 36.666667 2.6666667
y   1.333333  2.666667 0.2666667