On Oct 10, 2011, at 12:44 PM, Uwe Ligges wrote:
On 10.10.2011 18:10, Alexander Engelhardt wrote:
Hey list,
This might be a more general question and not that R-specific.
Sorry for
that.
I'm trying to draw a random vector of 4 numbers that sum up to 1.
My first approach was something like
a <- runif(1)
b <- runif(1, max=1-a)
c <- runif(1, max=1-a-b)
d <- 1-a-b-c
but this kind of distorts the results, right?
Would the following be a good approach?
w <- sample(1:100, 4, replace=TRUE)
w <- w/sum(w)
Yes, although better combine both ways to
w <- runif(4)
w <- w / sum(w)
For the non-statisticians in the audience like myself who didn't know
what that distribution might "look like" (it being difficult to
visualize densities on your 3-dimensional manifold in 4-space), here
is my effort to get an appreciation:
M4 <- matrix(runif(40000), ncol=4)
M4 <- M4/rowSums(M4)
# just a larger realization of Ligges' advice
colMeans(M4)
[1] 0.2503946 0.2499594 0.2492118 0.2504342
plot(density(M4[,1]))
lines(density(M4[,2]),col="red")
lines(density(M4[,3]),col="blue")
lines(density(M4[,4]),col="green")
plot(density(rowSums(M4[,1:2])))
plot(density(rowSums(M4[,1:3])))
plot(density(rowSums(M4[,2:4])))
# rather kewl results, noting that these are a reflecion around 0.5 of
the single vector densities.
Uwe Ligges
I'd prefer a general algorithm-kind of answer to a specific R
function
(if there is any). Although a function name would help too, if I can
sourcedive.
--
David Winsemius, MD
West Hartford, CT
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