Fréchet mean
Builds on Metric spaceExpected valueRandom variableSample mean
Definition
Let be a metric space and let be a random element of with for some . The Fréchet function of is for , an expected value. A Fréchet mean of is a point with For points and weights , a Fréchet mean is a minimiser of ; with equal weights it is the sample Fréchet mean.
Remarks
The condition on and the triangle inequality give for every . The set of Fréchet means may be empty or have several points. On a complete Riemannian manifold a local minimiser of is called a Karcher mean. Replacing by gives the Fréchet median.
Example: in with the Euclidean distance, , where is the sample mean. So the sample Fréchet mean is unique and equals .
Non-uniqueness: on the unit sphere with the great-circle distance, take two antipodal points and . If is at distance from , it is at distance from , and is smallest exactly at . So every point of the equator between them is a Fréchet mean, and the "midpoint" is not a single point.
Non-example: if is real with the Cauchy distribution, then for every . The moment condition fails, is infinite everywhere, and has no Fréchet mean, just as it has no ordinary mean.
Reading path
To understand this page from the ground up, read these 5 pages in order. The foundations come first.
Show the path as a graph
- no evidence level
- Expected value concept
- Metric space concept
- Random variable concept
- Sample mean concept
- Fréchet mean definition
Further reading
About this page
| Tag | KMBHAYAGZ9 |
|---|---|
| URI | m2://KMBHAYAGZ9 |
| Kind | definition |
| Writing | W0 stub |
| MSC | 62R20, 62R30 |
| Defines | Fréchet mean |
| Uses | Metric space, Expected value, Random variable, Sample mean |
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