Dear V. K. Chetty,

Perhaps I'm missing something but why wouldn't you just use a list of

matrices, as in the following?

---------- snip ---------

> set.seed(123) # for reproducibility

> (Matrices <- lapply(1:3, function(i) matrix(sample(1:50, 4), 2, 2)))

[[1]]

[,1] [,2]

[1,] 31 14

[2,] 15 3

[[2]]

[,1] [,2]

[1,] 42 37

[2,] 43 14

[[3]]

[,1] [,2]

[1,] 25 27

[2,] 26 5

> (Eigenvalues <- lapply(Matrices, function(x) eigen(x,

only.values=TRUE)$values))

[[1]]

[1] 37.149442 -3.149442

[[2]]

[1] 70.27292 -14.27292

[[3]]

[1] 43.3196 -13.3196

---------- snip ---------

I hope this helps,

John

John Fox, Professor Emeritus

McMaster University

Hamilton, Ontario, Canada

web:

https://socialsciences.mcmaster.ca/jfox/On 2021-03-29 5:28 p.m., Veerappa Chetty wrote:

> I want to use map and purr functions to compute eigen values for 3000

> matrices. Each matrix has 2 rows and 2 columns. The following code does not

> work.

>

> test.dat<- tibble(ID=c(1,2),a=c(1,1),b=c(1,1),c=c(2,2),d=c(4,3))

>

> test.out<-test.dat %>% nest(-ID) %>% mutate(fit = purrr::map(data,~

> function(x) eigen(matrix(x,2,2)), data=.))

>

> This must be a trivial question for current young practitioners ( In my 9

> th decade, I am having fun using R markdown and I am trying to continue my

> research!) I would greatly appreciate any help.

> Thanks.

> V.K.Chetty

>

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