Recent content by skwey

You are right, I shouldn't have used I(theta)=... But besides that I stand by the question. What I ment by many outcomes, Is that the fisher informtion, is the variance of what I wrote. So if the varince of what I wrote is high, then another way to say it, is that the expression I wrote have...

Thanks for your replies, and thanks for correcting my notation. I guess one can understand this, by looking at the inequality and the fact that it is the inverse of the minimum varince of an unbiased estimator. But I'd like to understand it directly from the equation. Let me reprhase the...

How to understand "fisher information"? Hello, I am trying to understand what "fisher information is." It is defined as V [∂/∂∅(lnf(X,∅)) ]=E[ (∂/∂∅[lnf(X,∅)])^2 ]. From Wikipedia: Can you please help me understand why this is the case? How can this be explained by looking at the...

Here is the question. I think my calculations in the first post is wrong, there I look at the mean of the difference of each run(where we look at both naomis time vs john or pauls.) but I think we should look at the difference of the means of Naomi vs the slowest of paul or john. That is...

Homework Statement 3 people John, Paul and Naomi enter simultaniously a postoffice. There are only 2 clerks there, john and paul go first. The service time is exponentially distributed with parameters lamda1 and lamda2. Naomi must wait uintil either John or Paul is finised. The time that...

Thanks for your contribution. I don't know about Jensens inequality, but you don't need it to show that r/(X+r) overestimates p: It is easy to show that E[(r-1)/(x+r-1)] is p. And also that r/(x+r) > (r-1)/(x+r-1) for all x>0, then it is logical that r/(x+r) overestimates p, because when you...

I see what you are saying Stephen Tashi, the sampling process obvioiusly alters the way we estimate, it is just interesting that it is so close to the binomial forumula except that you subtract 1 from r. Another thing that makes this make you wonder more is if you look at the expected value...

Hey, there's this thing I can't wrap my head around. Let's say we have a negative binomial variable x, with parameters p and r. That is, x is the number of failures we get before the rth sucess, while looking at random bernolli variables with sucsess rate p. It can be shown that...

The answer to your first question is yes. Your second link does not say anything about my problem. I found an explanation in the fist link but it is hard. If I try to use this explanation as a guide I get stuck: Ok, this is ok, I have 5 elements, A, B, C, D, E, I label them A=0, B=1,C=2...

Hello, is there any derivation on the net for the unordered with replacement formula? I've searcced but didnt find any. Ex: You have 5 different tickets and you shall choose 3 from a bowl. When one is chosen another like the chosen one is put in the bowl. The answer is 35, and the formula is...

Thanks! And that was a good example!

This is not a homework question. But a question on how to understand what my textbook does. It is about choosing the free variables. Let's say I have the system of equations: x1-2x2+3x3+2x4+x5 =10 x3 +2x5=-3 x4 -4x5=7 Then my book says that...

The l'Hopital part: ln[M(t/n)]' / (1/n) ' =[M'(t/n)*-t/n^2 / M(t/n)] / [-1/n^2]= M'(t/n)*t/M(t/n). As n-> infinity this becomes ut.

Hi I want to prove this using momentgenerating functions. I would like to do this without going into the standard normal distribution, just the normal distribution. I would like to show that the momentgenerating function of (x1+x2+x3...xn)/n--->e^(ut+sigma^2t/2) as n-->infinity. x1, x2...

When you write g(x)=E[f(x,Y)], do you mean g(x)=E[f(y|x)], where f(y|x) is the marginal distribution of y as a function of x?