Approximate distributions for maximum likelihood and maximum a posteriori estimates under a gaussian noise model

Craig K. Abbey, Eric W Clarkson, Harrison H Barrett, Stefan P. Müller, Frank J. Rybicki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

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 Cramér-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.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages167-175
Number of pages9
Volume1230
ISBN (Print)3540630465, 9783540630463
StatePublished - 1997
Event15th International Conference on Information Processing in Medical Imaging, IPMI 1997 - Poultney, United States
Duration: Jun 9 1997Jun 13 1997

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1230
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other15th International Conference on Information Processing in Medical Imaging, IPMI 1997
CountryUnited States
CityPoultney
Period6/9/976/13/97

Fingerprint

A Posteriori Estimates
Maximum a Posteriori
Gaussian Noise
Maximum likelihood
Maximum Likelihood
Conditional Distribution
Nonlinear Problem
Model
Lower bound
Estimate

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Abbey, C. K., Clarkson, E. W., Barrett, H. H., Müller, S. P., & Rybicki, F. J. (1997). Approximate distributions for maximum likelihood and maximum a posteriori estimates under a gaussian noise model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1230, pp. 167-175). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1230). Springer Verlag.

Approximate distributions for maximum likelihood and maximum a posteriori estimates under a gaussian noise model. / Abbey, Craig K.; Clarkson, Eric W; Barrett, Harrison H; Müller, Stefan P.; Rybicki, Frank J.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 1230 Springer Verlag, 1997. p. 167-175 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1230).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abbey, CK, Clarkson, EW, Barrett, HH, Müller, SP & Rybicki, FJ 1997, Approximate distributions for maximum likelihood and maximum a posteriori estimates under a gaussian noise model. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 1230, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1230, Springer Verlag, pp. 167-175, 15th International Conference on Information Processing in Medical Imaging, IPMI 1997, Poultney, United States, 6/9/97.
Abbey CK, Clarkson EW, Barrett HH, Müller SP, Rybicki FJ. Approximate distributions for maximum likelihood and maximum a posteriori estimates under a gaussian noise model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 1230. Springer Verlag. 1997. p. 167-175. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Abbey, Craig K. ; Clarkson, Eric W ; Barrett, Harrison H ; Müller, Stefan P. ; Rybicki, Frank J. / Approximate distributions for maximum likelihood and maximum a posteriori estimates under a gaussian noise model. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 1230 Springer Verlag, 1997. pp. 167-175 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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