Statistics Sufficiency and information Concept
Complete statistic
Summary
A statistic is complete when no non-trivial function of it has expectation zero under every parameter value. Completeness means that the family of laws of the statistic is rich enough to separate functions of it. It is the key hypothesis of the Lehmann–Scheffé theorem and of Basu's theorem. By Lehmann–Scheffé, an unbiased estimator that is a function of a complete sufficient statistic is the unique best one.
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About this page
| Tag | DED6JFAV1K |
|---|---|
| URI | m2://DED6JFAV1K |
| Kind | concept |
| Writing | W0 stub |
| MSC | 62B05 |
| Specializes | Statistic |
| Same as |
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What this page needs for W1
- an inventory row: the row of the inventory that the node accounts for (0 of 1)
- a source with a locator (0 of 1)
The writing levels say how complete the text of a page is. They do not measure its truth.