Statistics Estimator Consistency

  • Context: Graduate 
  • Thread starter Thread starter jmlink
  • Start date Start date
  • Tags Tags
    Statistics
Click For Summary
SUMMARY

The discussion centers on the consistency of estimators for a uniform distribution on the interval (Ө, Ө+1) and (0, Ө). It establishes that Ө1, defined as Ῡ - 0.5, and Ө2, defined as Yn - (n/(n+1)), are both consistent estimators of Ө. Additionally, it confirms that Yn, the maximum of a random sample from a power family distribution, is a consistent estimator of Ө, with its distribution function detailed as Fn(y) = (y/Ө)^(αn) for 0 ≤ y ≤ Ө.

PREREQUISITES
  • Understanding of uniform distributions and their properties
  • Familiarity with the concept of consistent estimators in statistics
  • Knowledge of maximum likelihood estimation techniques
  • Basic statistical notation and terminology
NEXT STEPS
  • Study the properties of consistent estimators in statistical theory
  • Learn about the uniform distribution and its applications in estimation
  • Explore maximum likelihood estimation methods in depth
  • Investigate the implications of power family distributions in statistical modeling
USEFUL FOR

Statisticians, data analysts, and researchers involved in statistical estimation and modeling, particularly those working with uniform and power family distributions.

jmlink
Messages
3
Reaction score
0
1) Distribution is a uniform distribution on the interval (Ө, Ө+1)
Show that Ө1 is a consistent estimator of Ө. Ө1=Ῡ -.5
Show that Ө2 is a consistent estimator of Ө. Ө2=Yn – (n/(n+1)).

2) I think the distribution for this one is a uniform distribution on the interval (0, Ө) but I am not 100% sure.
Let Y1, Y2, …, Yn denote a random sample of size n from a power family distribution. Then the method in Section 6.7 imply that Yn=max(Y1, Y2, …, Yn ) has the distribution function of:
0, y<0
Fn(y)= (y/ Ө)^(αn) , 0 ≤ y ≤ Ө
1, y> Ө

Show that Yn is a consistent estimator of Ө.
 
Last edited:
Physics news on Phys.org
For 1 and 2 you need to state the distribution being sampled.
 

Similar threads

  • · Replies 3 ·
Replies
3
Views
3K
  • · Replies 7 ·
Replies
7
Views
3K
  • · Replies 6 ·
Replies
6
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 3 ·
Replies
3
Views
10K
  • · Replies 1 ·
Replies
1
Views
2K
Replies
1
Views
4K
Replies
6
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K