What is your objective?.
to Find MLE.. We assume a distribution first and for estimation of parameters we use MLE
See this for more info.
Maximum likelihood - Wikipedia, the free encyclopedia
Does anyone know how to find maximum likelihood estimates? I have a sample with 15 values but am not understanding exactly what I am supposed to be looking for with the maximum likelihood estimates. Thanks for any potential help. I haven't come across an explanation that would help me tackle this problem.
What is your objective?.
to Find MLE.. We assume a distribution first and for estimation of parameters we use MLE
See this for more info.
Maximum likelihood - Wikipedia, the free encyclopedia
First you need the likelihood function, which in the continuous case id the product of the densities via independence.
In the discrete case you take the product of the distribution function.
Then, as it's name says, you maximize wrt the parameter.
In many cases that's just calculus.
But in a case where the parameter is a boundary in your support, then calculus fails, but common sense prevails.
I am to find the MLE estimates for and if a random sample of 15 from has the values 31.5, 36.9, 33.8, 30.1, 33.9, 35.2, 29.6, 34.4, 30.5, 34.2, 31.6, 36.7, 35.8, 34.5, 32.7
All I am coming up with is, for the mean,
...
Partil derivative=
0=
And similar equations for the variance leading me to
The mean calculated from the sample is 33.4267 and the variance is 5.0979, but all these equations are straight out of a book from the library, so I'm not sure if they had to be tweaked or are standard. Also, I could find what the k stood for. It wasn't explained anywhere near that section. Thanks