<abstract xmlns="http://www.w3.org/1999/xhtml"><p> Fisher information is of key importance in estimation theory. It is used as a tool for characterizing complex signals or systems, with applications, e.g. in biology, geophysics and signal processing. The problem of minimizing Fisher information in a set of distributions has been studied by many researchers. In this paper, based on some rather simple statistical reasoning, we provide an alternative proof for the fact that Gaussian distribution with finite variance minimizes the Fisher information over all distributions with the same variance.</p></abstract>

Fisher information is of key importance in estimation theory. It is used as a tool for characterizing complex signals or systems, with applications, e.g. in biology, geophysics and signal processing. The problem of minimizing Fisher information in a set of distributions has been studied by many researchers. In this paper, based on some rather simple statistical reasoning, we provide an alternative proof for the fact that Gaussian distribution with finite variance minimizes the Fisher information over all distributions with the same variance.

An Alternative Proof For the Minimum Fisher Information of Gaussian Distribution

Journal of Applied Mathematics, Statistics and Informatics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"An Alternative Proof For the Minimum Fisher Information of Gaussian Distribution"}

Fisher information is of key importance in estimation theory. It is used as a tool for characterizing complex signals or systems, with applications, e.g. in...

An Alternative Proof For the Minimum Fisher Information of Gaussian Distribution

Online veröffentlicht: 11. Jan. 2019

Seitenbereich: 5 - 10

DOI: https://doi.org/10.2478/jamsi-2018-0008

Schlüsselwörter
Fisher information, Gaussian distribution, Minimum risk equivariant estimator

© 2019 Abbas Pak, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

An Alternative Proof For the Minimum Fisher Information of Gaussian Distribution

Online veröffentlicht: 11. Jan. 2019

Seitenbereich: 5 - 10

DOI: https://doi.org/10.2478/jamsi-2018-0008

SchlüsselwörterFisher information, Gaussian distribution, Minimum risk equivariant estimator

© 2019 Abbas Pak, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
Fisher information, Gaussian distribution, Minimum risk equivariant estimator