R code Gaussian mixture -- numerical expression has 2 elements: only the first used - r

Question

I'm trying to create a Gaussian Mix function according to these parameters:
For each sample, roll a die with k sides
If the j-th side appears from the roll, draw a sample from Normal(muj, sdj) where muj and sdj are the mean and standard deviation for the j-th Normal distribution respectively. This means you should have k different Normal distributions to choose from. Note that muj is the mathematical form of referring to the j-th element in a vector called mus.
The resulting sample from this Normal is then from a Gaussian Mixture.
Where:
n, an integer that represents the number of independent samples you want from this random variable
mus, a numeric vector with length k
sds, a numeric vector with length k
prob, a numeric vector with length k that indicates the probability of choosing the different Gaussians. This should have a default to NULL.
This is what I came up with so far:
n <- c(1)
mus <- c()
sds <- c()
prob <- c()
rgaussmix <- function(n, mus, sds, prob = NULL){
if(length(mus) != length(sds)){
stop("mus and sds have different lengths")
}
for(i in 1:seq_len(n)){
if(is.null(prob)){
rolls <- c(NA, n)
rolls <- sample(c(1:length(mus)), n, replace=TRUE)
avg <- rnorm(length(rolls), mean=mus[rolls], sd=sds[rolls])
}else{
rolls <- c(NA, n)
rolls <- sample(c(1:length(mus), n, replace=TRUE, p=prob))
avg <- rnorm(length(rolls), mean=mus[rolls], sd=sds[rolls])
}
}
return(avg)
}
rgaussmix(2, 1:3, 1:3)
It seems to match most of the requirements, but it keeps giving me the following error:
numerical expression has 2 elements: only the first usednumber of items to replace is not a multiple of replacement length
I've tried looking at the lengths of multiple variables, but I can't seem to figure out where the error is coming from!
Could someone please help me?

Answer 1

If you do seq_len(2) it gives you:
[1] 1 2
And you cannot do 1:(1:2) .. it doesn't make sense
Also you can avoid the loops in your code, by sampling the number of tries you need, for example if you do:
rnorm(3,c(0,10,20),1)
[1] -0.507961 8.568335 20.279245
It gives you 1st sample from the 1st mean, 2nd sample from 2nd mean and so on. So you can simplify your function to:
rgaussmix <- function(n, mus, sds, prob = NULL){
if(length(mus) != length(sds)){
stop("mus and sds have different lengths")
}
if(is.null(prob)){
prob = rep(1/length(mus),length(mus))
}
rolls <- sample(length(mus), n, replace=TRUE, p=prob)
avg <- rnorm(n, mean=mus[rolls], sd=sds[rolls])
avg
}
You can plot the results:
plot(density(rgaussmix(10000,c(0,5,10),c(1,1,1))),main="mixture of 0,5,10")