I would like to solve the equation is is the sum from k = i to N of
choose(N,k) * MR ^ k * (1 - MR) ^ (N - k) - 0.50 = 0
I want to solve for MR. This seems like a non-linear equation to me. But I am
having a hard time writing the function that implements the above. I could use
'for(...) as a brute force appoarch but I would like a more "elegant" solution.
The variables 'N' and 'i' are basically constant so the function has to take
these from some kind of global space. So if I take t brute force apporach I
came up with:
f <- function(MR)
{
k <- i:N
return sum(choose(N,k) * MR ^ k * (1 - MR) ^ (N - k)) - 0.5
}
Does this seem like a reasonable implemetation? How are 'N' and 'i' declare as
"global"? For each equation N and I are constant but I want to be able to
modify them. In other words solve the equantion after setting N to 6 and i to 5
then again after setting i to 4.
The next question is regarding which 'R' function would be best suited to
solving this equation? I looked at 'nls' but that seems to take data as an
input. I want to solve the equation. What other options do I have? There must
be an 'R' function to solve a non-linear equation. I did
help.search("non-linear") and the closest match was nlm. But nlm minimizes the
function rather than solving it.
Ideas?
Thank you.
Kevin
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