The professor gave us an exercise but for me it's not totally clear.
I have a distribution function which depend on a parameter X that I need to estimate. The function describes the distribution of angles Y of which I know a sample Y1,..YN.
In order to estimate X, our professor told us to divide the sample in small groups ( of 3 or 4) .
For example, I consider Y1,Y2,Y3,Y4. Using these four, I consider the maximum likelihood method to obtain an estimate of X. We call the estimate obtained from the first 4 samples X1 and Z1 the mean of Y1,Y2,Y3,Y4.
By iterating this procedure, I find a vector of estimated parameters Xi and a vector with the means of the small groups Zi.
After that I have to do a linear regression (I used the lm function from R), because the final goal was to obtain a formula that relates X to the means Z, which is because we had divided the sample in small groups.
The professor told us that what we do is, more or less, an application of the generalized method of moments and we have to explain how we are using this method, but for me it's not so clear, can someone please help me? Thanks.
- Badges
- Science topic
- Similar topics
- Mathematics