How can I solve this equation using the Fisher Information?

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    Derivative Integral
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Discussion Overview

The discussion revolves around understanding a specific equation related to Fisher Information and its application in statistical estimation. Participants seek clarification on the components of the equation and their meanings, particularly focusing on the likelihood function and the role of the parameter r.

Discussion Character

  • Exploratory, Technical explanation, Conceptual clarification

Main Points Raised

  • One participant expresses confusion about an equation and requests assistance in understanding it.
  • Another participant questions whether r is a function.
  • A participant clarifies that f(X;r) represents a likelihood function of sample X given a known value r, and mentions that r with a dot above is an unbiased estimator of r.
  • There is a suggestion that r' may not be a function of r.
  • One participant claims to have solved the equation and found the answer related to the Fisher Information proving topic.

Areas of Agreement / Disagreement

The discussion shows a mix of confusion and clarification, with no consensus on the interpretation of all components of the equation. While one participant claims to have solved the equation, others are still seeking understanding.

Contextual Notes

Some assumptions about the definitions of the likelihood function and the parameters involved may be missing, and the discussion does not resolve all mathematical steps or interpretations.

MythSquare
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Can someone explain to me this equation I stuck with. I can't get the right part of it.
http://img194.imageshack.us/img194/5840/ajhvekf.png
 
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r is a function or what?
 
ohh yes the main part...sry
f(X;r) is a likelihood function of sample X given known value r.
r with dot above is unbiased estimator of r

I think f is likelihood function of data set given value r.
 
Last edited:
r' is probably not a function of r.
 
Thx to all who have tried to help me with this.-)
I solved this equation.
I found the answer on the Fisher Information proving topic.
 

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