Conditional mean estimates and Bayesian hypothesis testing (Corresp.)
- 1 November 1975
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Information Theory
- Vol. 21 (6) , 663-665
- https://doi.org/10.1109/tit.1975.1055462
Abstract
For conditional probability density functions (pdf's) drawn from the exponential family, it is shown that the marginal pdf is completely determined by a posterior conditional mean estimate (CME). This result implies that likelihood ratios involving these marginals have the estimator-correlator structure in the following sense: if the noise is drawn from an exponential pdf, then independent of the signal (prior pdf), the optimum detector correlates the estimate with the data. A generalization of Esposito's result on "pseudoestimates" is also given.Keywords
This publication has 3 references indexed in Scilit:
- A general likelihood-ratio formula for random signals in Gaussian noiseIEEE Transactions on Information Theory, 1969
- On a relation between detection and estimation in decision theoryInformation and Control, 1968
- A class of estimators for optimum adaptive detectionInformation and Control, 1967