Create a Correlation Matrix From a Correlation Vector in R -


i want create correlation matrix given correlation vector, upper (or lower) triangular matrix of correlation matrix.

the goal transform vector

enter image description here

to correlation matrix 1s on diagonal.

enter image description here

do know if there method creating matrix given triangular above diagonal , set diagonal 1?

i don't know if there automatic way this, expanding on comment:

myvec <- c(-.55, -.48, .66, .47, -.38, -.46) mempty <- matrix(0, nrow = 4, ncol = 4) mindex <- matrix(1:16, nrow = 4, ncol = 4) mempty[mindex[upper.tri(mindex)]] <- myvec mempty[lower.tri(mempty)] <- t(mempty)[lower.tri(t(mempty))] diag(mempty) <- 1 mempty #       [,1]  [,2]  [,3]  [,4] # [1,]  1.00 -0.55 -0.48  0.47 # [2,] -0.55  1.00  0.66 -0.38 # [3,] -0.48  0.66  1.00 -0.46 # [4,]  0.47 -0.38 -0.46  1.00

here's hacked function. hope mathematics steps correct!

vec2symmat <- function(invec, diag = 1, byrow = true) {   nrow <- ceiling(sqrt(2*length(invec)))    if (!sqrt(length(invec)*2 + nrow) %% 1 == 0) {     stop("invec wrong length create square symmetrical matrix")   }    mempty <- matrix(0, nrow = nrow, ncol = nrow)   mindex <- matrix(sequence(nrow^2), nrow = nrow, ncol = nrow, byrow = byrow)   if (istrue(byrow)) {     mempty[mindex[lower.tri(mindex)]] <- invec     mempty[lower.tri(mempty)] <- t(mempty)[lower.tri(t(mempty))]   } else {     mempty[mindex[upper.tri(mindex)]] <- invec     mempty[lower.tri(mempty)] <- t(mempty)[lower.tri(t(mempty))]   }    diag(mempty) <- diag   mempty }

here different value diagonal. 

vec2symmat(1:3, diag = na) #      [,1] [,2] [,3] # [1,]   na    1    2 # [2,]    1   na    3 # [3,]    2    3   na

here's error message if try provide data can't create square matrix.

vec2symmat(1:4) # error in vec2symmat(1:4) :  #   invec wrong length create square symmetrical matrix

and, default settings.

vec2symmat(1:10) #      [,1] [,2] [,3] [,4] [,5] # [1,]    1    1    2    3    4 # [2,]    1    1    5    6    7 # [3,]    2    5    1    8    9 # [4,]    3    6    8    1   10 # [5,]    4    7    9   10    1

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