BAYESIAN STATISTICAL DECISION THEORY AND RELIABILITY-BASED DESIGN

1972 ◽  
pp. 47-68 ◽  
Author(s):  
C. ALLIN CORNELL
Keyword(s):  
Decision Theory ◽  
Statistical Decision Theory ◽  
Statistical Decision ◽  
Reliability Based Design ◽  
Bayesian Statistical Decision Theory

scholarly journals Bayesian natural selection and the evolution of perceptual systems

2002 ◽  
Vol 357 (1420) ◽  
pp. 419-448 ◽  
Author(s):  
Wilson S. Geisler ◽  
Randy L. Diehl
Keyword(s):  
Natural Selection ◽  
Decision Theory ◽  
Ideal Observer ◽  
Statistical Decision Theory ◽  
Statistical Decision ◽  
Natural Stimuli ◽  
Ideal Observers ◽  
Formal Framework ◽  
Bayesian Statistical Decision Theory ◽  
Perceptual Systems

In recent years, there has been much interest in characterizing statistical properties of natural stimuli in order to better understand the design of perceptual systems. A fruitful approach has been to compare the processing of natural stimuli in real perceptual systems with that of ideal observers derived within the framework of Bayesian statistical decision theory. While this form of optimization theory has provided a deeper understanding of the information contained in natural stimuli as well as of the computational principles employed in perceptual systems, it does not directly consider the process of natural selection, which is ultimately responsible for design. Here we propose a formal framework for analysing how the statistics of natural stimuli and the process of natural selection interact to determine the design of perceptual systems. The framework consists of two complementary components. The first is a maximum fitness ideal observer, a standard Bayesian ideal observer with a utility function appropriate for natural selection. The second component is a formal version of natural selection based upon Bayesian statistical decision theory. Maximum fitness ideal observers and Bayesian natural selection are demonstrated in several examples. We suggest that the Bayesian approach is appropriate not only for the study of perceptual systems but also for the study of many other systems in biology.

Measurement of radioactive samples: application of the Bayesian statistical decision theory

Metrologia ◽  
2005 ◽  
Vol 42 (5) ◽  
pp. 442-448 ◽  
Author(s):  
Jean-Pascal Laedermann ◽  
Jean-François Valley ◽  
François O Bochud
Keyword(s):  
Decision Theory ◽  
Statistical Decision Theory ◽  
Statistical Decision ◽  
Bayesian Statistical Decision Theory
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