Using brute force method, I have to find the maximum likelihood estimates where: we have to vary µ from 5 to 15 and σ from 0.5 to 1.5, both in increments of 0.1 This is what I have so far:
data = 8.453532, 10.025041,11.495339, 9.367600, 8.333229, 9.788753, 10.883344, 10.543059, 9.869095, 10.799819
mu = seq(5, 15, 0.1)
sigma = seq(0.5, 1.5, 0.1)
neglog <- array(dim=c(mu), dim=c(sigma))
Any idea how to continue the code?
You can list all possible unique combinations of two vectors by:
res <- expand.grid(mu, sigma)
names(res) <- c("mu", "sigma")
res
mu sigma
1 5.0 0.5
2 5.1 0.5
3 5.2 0.5
4 5.3 0.5
5 5.4 0.5
6 5.5 0.5
... ...
1107 14.6 1.5
1108 14.7 1.5
1109 14.8 1.5
1110 14.9 1.5
1111 15.0 1.5
Probably one can use expand.grid to find all combination of the indexes:
indexes <- expand.grid(seq(mu), seq(sigma))
names(indexes) <- c("mu", "sigma")
# use the indexes to get the actual values
indexes$mu <- mu[indexes$mu]
indexes$sigma <- sigma[indexes$sigma]
# call the data frame as `res`ult
res <- indexes
# now `res` contains all the combinations of the values of `mu` and `sigma`.
But you could use a normal nested for loop
res <- array(dim=c(length(mu) * length(sigma), 2))
idx <- 0
for (i in seq(mu)) {
for (j in seq(sigma)) {
idx <- idx + 1
res[idx,] <- c(mu[i], sigma[j])
}
}
# then `res` contains all combinations!
