How to Find the Conditional Density for an Improved Estimator?

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SUMMARY

The discussion centers on finding the conditional density for an improved estimator derived from a family of densities defined as $f(x,\theta)=\frac{exp(-{\sqrt{x}})}{{\theta}}$. The participant establishes that ${\sqrt{X_{1}}}/2$ serves as an unbiased estimator and identifies $T(X)={\sqrt{X_{1}}}+..+{\sqrt{X_{n}}}$ as a sufficient statistic for $\theta$. Utilizing the Rao-Blackwell theorem, the improved estimator is determined to be $E({\sqrt{x}}/2|T)$. The participant initially questions the validity of the density function but later resolves the issue independently.

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  • Familiarity with unbiased estimators
  • Knowledge of sufficient statistics
  • Basic concepts of conditional density functions
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Statisticians, data scientists, and researchers involved in statistical estimation and inference, particularly those interested in improving estimators using the Rao-Blackwell theorem.

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Consider a family of densitites $f(x,\theta)=\frac{exp(-{\sqrt{x}})}{{\theta}}$. Let $X_{1}$ be a single observation from this family. I have shown that ${\sqrt{X_{1}}}/2$ is an unbiased estimator. Now consider $n$ observations $X_{1},..X_{n}$. I have shown that $T(X)={\sqrt{X_{1}}}+..+{\sqrt{X_{n}}}$ is a sufficient statistic for $\theta$. Now use the Rao Blackwell theorem to find an improved estimator.

The improved estimator is $E({\sqrt{x}}/2|T)$. For this I need the conditional density. How do I find this?

Thanks
 
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Are you sure $$f(x,\theta)$$ is a family of densities?
 
stainburg said:
Are you sure $$f(x,\theta)$$ is a family of densities?

I got the density completely wrong. Anyway I have just found a way to do the question.
 

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