@inproceedings{7993e10e34da4345a45c03d3c9459539,
title = "Approximate distributions for maximum likelihood and maximum a posteriori estimates under a gaussian noise model",
abstract = "The performance of Maximum Likelihood (ML) and Maximum a posteriori (MAP) estimates in nonlinear problems at low data SNR is not well predicted by the Cram{\'e}r-Rao or other lower bounds on variance. In order to better characterize the distribution of ML and MAP estimates under these conditions, we derive an approximate density for the conditional distribution of such estimates. In one example, this approximate distribution captures the essential features of the distribution of ML and MAP estimates in the presence of Gaussian-distributed noise.",
author = "Abbey, {Craig K.} and Eric Clarkson and Barrett, {Harrison H.} and M{\"u}ller, {Stefan P.} and Rybicki, {Frank J.}",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 1997.; 15th International Conference on Information Processing in Medical Imaging, IPMI 1997 ; Conference date: 09-06-1997 Through 13-06-1997",
year = "1997",
doi = "10.1007/3-540-63046-5_13",
language = "English (US)",
isbn = "3540630465",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer-Verlag",
pages = "167--175",
editor = "James Duncan and Gene Gindi",
booktitle = "Information Processing in Medical Imaging - 15th International Conference, IPMI 1997, Proceedings",
}