Cramer-Rao lower boundry ion;

  • Thread starter Sander1337
  • Start date
  • Tags
    Ion
This means that the Cramer-Rao lower boundry is simply -n*θ^(-2), or in other words, -n/θ^2.In summary, the assignment is to calculate the Cramer-Rao lower boundry for consistent estimators of θ. The Cramer-Rao lower boundry is found by taking the expected value of the second derivative of the natural logarithm of the distribution function. The expected value is -θ^(-2) and the final Cramer-Rao lower boundry is -n/θ^2.
  • #1
Sander1337
10
0
Hi there,

I've got a distribution function for an assignment for my school here and I don't get the hang of the question;

f(x) = θ* 2^θ * x^(-θ-1) for x>2
0 for else

The assignment is to calculate the Cramer-Rao lower boundry for consistent estimators of θ.

This is what we've got so far;

Cramer-Rao lower boundry:
[-n*E[d^2/dθ^2 ln(f(y))]]^-1

(d^2/dθ^2)ln(f(x)) = -θ^(-2)= CRLB function

Now since our professor didn't explain the Cramer Rao lower boundry we haven't got a clue of how to continue now. Is there someone here who knows how to continue now?

Greetings,

Tony, Siebe & Sander

(question might be in wrong (sub)forum, apoligies for that, don't bother rerouting this question to the right (sub)forum, thanks!)
 
Last edited:
Physics news on Phys.org
  • #2
Well, the next step is to take the expected value (with respect to x). Since -θ^(-2) does not involve x, it is just a constant, so the expected value is -θ^(-2) itself.
 

1. What is the Cramer-Rao lower bound?

The Cramer-Rao lower bound is a theoretical lower limit on the variance of any unbiased estimator of a parameter in a statistical model. It provides a benchmark for evaluating the efficiency of an estimator, with lower values indicating higher efficiency.

2. How is the Cramer-Rao lower bound calculated?

The Cramer-Rao lower bound is calculated as the reciprocal of the Fisher information matrix, which is the expected value of the second derivative of the log-likelihood function with respect to the parameter being estimated. This calculation involves taking partial derivatives and evaluating expectations, and can be complex for more complicated models.

3. What is the significance of the Cramer-Rao lower bound in statistical inference?

The Cramer-Rao lower bound is important in statistical inference as it provides a fundamental limit on the accuracy of estimators. If an estimator has a variance that is equal to the Cramer-Rao lower bound, then it is considered to be a "minimum variance unbiased estimator" (MVUE), meaning that it is the most efficient estimator possible.

4. Can the Cramer-Rao lower bound be violated?

Yes, the Cramer-Rao lower bound can technically be violated in some cases. This can happen if the assumptions of the statistical model are not met or if the estimator is biased. However, in most cases, the Cramer-Rao lower bound serves as a useful theoretical benchmark for evaluating the performance of estimators.

5. How is the Cramer-Rao lower bound used in practical applications?

The Cramer-Rao lower bound is commonly used in statistical applications to compare the efficiency of different estimators. It can also be used to derive the asymptotic variance of an estimator, which is useful for constructing confidence intervals and conducting hypothesis tests. Additionally, it can be used to assess the efficiency of sample designs and to guide the selection of optimal sample sizes.

Similar threads

  • Set Theory, Logic, Probability, Statistics
Replies
4
Views
2K
  • Introductory Physics Homework Help
Replies
3
Views
1K
Replies
3
Views
329
  • Electromagnetism
Replies
1
Views
719
  • Advanced Physics Homework Help
Replies
1
Views
1K
  • Calculus and Beyond Homework Help
Replies
21
Views
2K
Replies
1
Views
1K
  • Advanced Physics Homework Help
Replies
4
Views
1K
  • Introductory Physics Homework Help
Replies
8
Views
2K
  • Calculus and Beyond Homework Help
Replies
5
Views
1K
Back
Top