Name
Title | ||
|---|---|---|
Estimation of Bounded Normal Mean: An Alternative Proof for the Discreteness of the Least Favorable Prior |
Abstract | ||
|---|---|---|
This paper studies the classical Bayesian normal mean estimation problem where the estimand is assumed to be contained in a bounded set. It is known that the least favorable distribution for this mean estimation problem is discrete with finitely many mass points. This work offers an alternative proof utilizing the variational diminishing property of Gaussian kernels. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ITW44776.2019.8988927 | 2019 IEEE Information Theory Workshop (ITW) |
Keywords | Field | DocType |
classical Bayesian normal mean estimation problem,bounded set,favorable distribution,alternative proof,bounded normal mean,discreteness,Gaussian kernels | Discrete mathematics,Mean estimation,Estimand,Computer science,Bounded set,Gaussian,Bounded function,Bayesian probability | Conference |
ISSN | ISBN | Citations |
2475-420X | 978-1-5386-6901-3 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Semih Yagli | 1 | 0 | 0.34 |
| Alex Dytso | 2 | 45 | 20.03 |
| H. V. Poor | 3 | 25411 | 1951.66 |