Petr -
Yes, you are interpreting the second suggestion exactly correctly,
apart from concern for possible correlations among x1,x2,x3.
If one can treat them as independent, I would do exactly as you
show: generate a vector of, say, n = 1 simulated draws from
x1, another vector of the same le
Hallo Thomas
Thank you for your answer, even I am not sure how to do it in R (or maybe at
all). My mathematics background is only faint so I drop the first possibility which
is for me rather cryptic.
Does your second suggestion mean:
1: compute random variable y <- f(rnorm(n,mymeanx1,my
Petr -
Very briefly, I think of three ways to approximate the standard
deviation of y = f(x1,x2,x3).
(1) linearise f() and use the covariance matrix of [x1,x2,x3].
(2) simulate draws from the joint distribution of [x1,x2,x3],
then compute the sample std dev of resulting f()s.
(3)
Dear all
Please, can you advice me how to compute an error, standard deviation or
another measure of variability of computed value.
I would like to do something like:
var(y) = some.function(var(x1),var(x2),var(x3))
for level F1 (2,3,...)
Let say I have some variables - x1, x2, x3 (two compute
