- #1
semidevil
- 157
- 2
I have a big test coming up, regarding estimators, but I just can't figure out the basics of maximum likilieehood.
so given this example, is this right?
p(k;theta) = theta^k * (1 - theta)^(1 - k), k = 0 1, and 0 < theta < 1.
so it's just the product of the function, and I get:
theta^K * 1 - (theta)^(sum from 1 to n of (k - n)).
then I take the natural log, and differentiate it to get
k/theta + (k - n)/ (1 - theta) = 0.
now, all I need to do is to put it in terms of theta...
first, did I do the first part right? in terms of finding the likelihoo function?
there's a lot of variables and I get confused when I do the products
so given this example, is this right?
p(k;theta) = theta^k * (1 - theta)^(1 - k), k = 0 1, and 0 < theta < 1.
so it's just the product of the function, and I get:
theta^K * 1 - (theta)^(sum from 1 to n of (k - n)).
then I take the natural log, and differentiate it to get
k/theta + (k - n)/ (1 - theta) = 0.
now, all I need to do is to put it in terms of theta...
first, did I do the first part right? in terms of finding the likelihoo function?
there's a lot of variables and I get confused when I do the products