Category:Definitions/Minimum Variance Unbiased Estimators
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This category contains definitions related to Minimum Variance Unbiased Estimators.
Related results can be found in Category:Minimum Variance Unbiased Estimators.
Let $S$ be a sample of $n$ observations from a probability distribution with frequency function $\map f {x, \theta}$.
Let it be assumed that certain regularity conditions apply.
Let it also be assumed that the extremes do not depend on $\theta$.
This article, or a section of it, needs explaining. In particular: what those conditions are You can help $\mathsf{Pr} \infty \mathsf{fWiki}$ by explaining it. To discuss this page in more detail, feel free to use the talk page. When this work has been completed, you may remove this instance of {{Explain}} from the code. |
Let $T$ be an unbiased estimator such that:
- $\var T = \dfrac 1 I$
where:
- $I = -n \map E {\dfrac {\partial^2 \ln f} {\partial \theta^2} }$
Then $\var T$ is called a minimum variance unbiased estimator.
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