Next Article in Journal
Thermodynamic Analysis of Resources Used in Thermal Spray Processes: Energy and Exergy Methods
Next Article in Special Issue
Structures in Sound: Analysis of Classical Music Using the Information Length
Previous Article in Journal
A PUT-Based Approach to Automatically Extracting Quantities and Generating Final Answers for Numerical Attributes
Previous Article in Special Issue
The Fisher Thermodynamics of Quasi-Probabilities
Article Menu

Export Article

Open AccessReview
Entropy 2016, 18(6), 236; doi:10.3390/e18060236

Generalisations of Fisher Matrices

Imperial Centre for Inference and Cosmology (ICIC), Imperial College London, Blackett Laboratory, Prince Consort Road, London SW7 2AZ, UK
Academic Editor: Takuya Yamano
Received: 3 May 2016 / Revised: 16 June 2016 / Accepted: 18 June 2016 / Published: 22 June 2016
(This article belongs to the Special Issue Applications of Fisher Information in Sciences)
View Full-Text   |   Download PDF [509 KB, uploaded 22 June 2016]   |  

Abstract

Fisher matrices play an important role in experimental design and in data analysis. Their primary role is to make predictions for the inference of model parameters—both their errors and covariances. In this short review, I outline a number of extensions to the simple Fisher matrix formalism, covering a number of recent developments in the field. These are: (a) situations where the data (in the form of ( x , y ) pairs) have errors in both x and y; (b) modifications to parameter inference in the presence of systematic errors, or through fixing the values of some model parameters; (c) Derivative Approximation for LIkelihoods (DALI) - higher-order expansions of the likelihood surface, going beyond the Gaussian shape approximation; (d) extensions of the Fisher-like formalism, to treat model selection problems with Bayesian evidence. View Full-Text
Keywords: fisher matrices; statistics; experimental design fisher matrices; statistics; experimental design
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Heavens, A. Generalisations of Fisher Matrices. Entropy 2016, 18, 236.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top