Generate N random integers that sum to M in R

by

Normalize.

rand_vect <- function(N, M, sd = 1, pos.only = TRUE) {
  vec <- rnorm(N, M/N, sd)
  if (abs(sum(vec)) < 0.01) vec <- vec + 1
  vec <- round(vec / sum(vec) * M)
  deviation <- M - sum(vec)
  for (. in seq_len(abs(deviation))) {
    vec[i] <- vec[i <- sample(N, 1)] + sign(deviation)
  }
  if (pos.only) while (any(vec < 0)) {
    negs <- vec < 0
    pos  <- vec > 0
    vec[negs][i] <- vec[negs][i <- sample(sum(negs), 1)] + 1
    vec[pos][i]  <- vec[pos ][i <- sample(sum(pos ), 1)] - 1
  }
  vec
}

For a continuous version, simply use:

rand_vect_cont <- function(N, M, sd = 1) {
  vec <- rnorm(N, M/N, sd)
  vec / sum(vec) * M
}

Examples

rand_vect(3, 50)
# [1] 17 16 17

rand_vect(10, 10, pos.only = FALSE)
# [1]  0  2  3  2  0  0 -1  2  1  1

rand_vect(10, 5, pos.only = TRUE)
# [1] 0 0 0 0 2 0 0 1 2 0

rand_vect_cont(3, 10)
# [1] 2.832636 3.722558 3.444806

rand_vect(10, -1, pos.only = FALSE)
# [1] -1 -1  1 -2  2  1  1  0 -1 -1

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