I am trying to simulate the forecast (rather than taking mean) using this code:
set.seed(100)
df <- data.frame("lower" = c(-1, 0.5, 0), "upper" = c(0, 2, 4), "mean" = c(-0.5, 1.2, 2.5))
df$simulation <- rnorm(1, df$mean, (df$upper - df$lower) / 2 / 1.96)
df
# lower upper mean simulation
#1 -1.0 0 -0.5 -0.6281103
#2 0.5 2 1.2 -0.6281103
#3 0.0 4 2.5 -0.6281103
I get same value in the simulation column.
However, if I provide the vector in the n parameter I get result that looks better:
df$simulation <- rnorm(nrow(df), df$mean, (df$upper - df$lower) / 2 / 1.96)
df
# lower upper mean simulation
#1 -1.0 0 -0.5 -0.6281103
#2 0.5 2 1.2 1.2503308
#3 0.0 4 2.5 2.4194724
Is the later solution is the right way of doing this?
