BibTex format
@article{Heavens:2016:10.3390/e18060236,
author = {Heavens, A},
doi = {10.3390/e18060236},
journal = {Entropy},
title = {Generalisations of Fisher Matrices},
url = {http://dx.doi.org/10.3390/e18060236},
volume = {18},
year = {2016}
}
Publications
Citation
RIS format (EndNote, RefMan)
TY - JOUR
AB - 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.
AU - Heavens,A
DO - 10.3390/e18060236
PY - 2016///
SN - 1099-4300
TI - Generalisations of Fisher Matrices
T2 - Entropy
UR - http://dx.doi.org/10.3390/e18060236
UR - http://hdl.handle.net/10044/1/38677
VL - 18
ER -