I have a list of elements in R as follows:
set.seed(123)
A <- matrix(rnorm(20 * 20, mean = 0, sd = 1), 20, 20)
B <- matrix(rnorm(20 * 20, mean = 0, sd = 1), 20, 20)
C <- matrix(rnorm(20 * 20, mean = 0, sd = 1), 20, 20)
D <- matrix(rnorm(20 * 20, mean = 0, sd = 1), 20, 20)
E <- matrix(rnorm(20 * 20, mean = 0, sd = 1), 20, 20)
DATA <- list(A,B,C,D,E)
I want for each matrix (A,B,...,E) to find the eigenvalues and combine them in a data frame as follows:
ei1 <- eigen(DATA[[1]])
ei1 <- round(ei1$values, 2)
eigenvalues1 <- as.data.frame(ei1)
ei2 <- eigen(DATA[[2]])
ei2 <- round(ei2$values, 2)
eigenvalues2 <- as.data.frame(ei2)
ei3 <- eigen(DATA[[3]])
ei3 <- round(ei3$values, 2)
eigenvalues3 <- as.data.frame(ei3)
ei4 <- eigen(DATA[[4]])
ei4 <- round(ei4$values, 2)
eigenvalues4 <- as.data.frame(ei4)
ei5 <- eigen(DATA[[5]])
ei5 <- round(ei5$values, 2)
eigenvalues5 <- as.data.frame(ei5)
eigenavules <-
cbind(eigenvalues1,eigenvalues2,eigenvalues3,eigenvalues4,eigenvalues5
)
How can I make this procedure automatically with the apply (or similar) function in instead of manually like above?
We may use lapply to loop over the list and apply the function, extract the eigen values and then do the conversion to data.frame at the end
eigenvalues <- as.data.frame(do.call(cbind,
lapply(DATA, function(x) round(eigen(x)$values, 2))))
-output
> eigenvalues
V1 V2 V3 V4 V5
1 1.77+3.73i 5.33+0.00i 5.11+0.00i -2.52+3.53i -1.87+4.42i
2 1.77-3.73i 1.72+4.13i -5.08+0.00i -2.52-3.53i -1.87-4.42i
3 -0.50+3.97i 1.72-4.13i 2.41+3.87i 2.12+3.32i 2.96+3.44i
4 -0.50-3.97i -4.02+1.85i 2.41-3.87i 2.12-3.32i 2.96-3.44i
5 -3.38+2.06i -4.02-1.85i -2.60+3.46i 3.72+0.00i -4.15+0.00i
6 -3.38-2.06i -3.27+0.00i -2.60-3.46i -3.16+0.30i 1.67+3.35i
7 3.89+0.00i 1.48+2.89i 0.10+3.78i -3.16-0.30i 1.67-3.35i
8 -2.47+3.00i 1.48-2.89i 0.10-3.78i 2.50+1.89i 3.28+1.47i
9 -2.47-3.00i 3.05+0.00i 3.74+0.00i 2.50-1.89i 3.28-1.47i
10 3.51+0.00i -0.97+2.79i 2.38+2.10i -2.69+1.46i -2.88+1.40i
11 2.04+2.29i -0.97-2.79i 2.38-2.10i -2.69-1.46i -2.88-1.40i
12 2.04-2.29i -1.86+2.07i -2.44+0.01i -1.04+2.51i -1.32+2.89i
13 -3.03+0.00i -1.86-2.07i -2.44-0.01i -1.04-2.51i -1.32-2.89i
14 -1.97+1.67i -2.18+0.00i -1.52+1.78i 0.69+2.32i -0.77+2.12i
15 -1.97-1.67i 2.14+0.00i -1.52-1.78i 0.69-2.32i -0.77-2.12i
16 0.81+1.91i 1.61+0.77i 1.93+0.86i 2.23+0.85i 1.40+1.09i
17 0.81-1.91i 1.61-0.77i 1.93-0.86i 2.23-0.85i 1.40-1.09i
18 1.02+0.00i 0.14+1.55i -0.04+1.88i -0.77+0.57i 0.65+0.35i
19 -0.57+0.47i 0.14-1.55i -0.04-1.88i -0.77-0.57i 0.65-0.35i
20 -0.57-0.47i -0.99+0.00i 0.26+0.00i 0.67+0.00i 0.58+0.00i