Improved posterior probability estimates from prior and conditional linear constraint systems

1991 ◽  
Vol 21 (2) ◽  
pp. 464-469 ◽  
Author(s):  
P. Snow
2021 ◽  
Author(s):  
Bonnie A. Armstrong

Aging is associated with an increase in the frequency of medical screening tests. Bayesian inference is used to estimate posterior probabilities of medical tests such as positive or negative predictive values (PPVs or NPVs). Both laypeople and experts are typically poor at estimating PPVs and NPVs when relevant probabilities are communicated descriptively. Decision making research has revealed dissociations between described and experience-based judgments. This study examined the accuracy of posterior probability estimates of 80 younger and 81 older adults when statistical information was presented through description or experience. Results show that both younger and older adults can make more accurate posterior probability estimates if they experience probabilities compared to when probabilities are described as either natural frequencies or conditional probabilities. Results also indicate that most people prefer to rely on physicians to make their medical decisions regardless of how confident they are in their judgments of probabilities.


2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Xianqing Chen ◽  
Lenan Wu

The extended binary phase shift keying (EBPSK) is an efficient modulation technique, and a special impacting filter (SIF) is used in its demodulator to improve the bit error rate (BER) performance. However, the conventional threshold decision cannot achieve the optimum performance, and the SIF brings more difficulty in obtaining the posterior probability for LDPC decoding. In this paper, we concentrate not only on reducing the BER of demodulation, but also on providing accurate posterior probability estimates (PPEs). A new approach for the nonlinear demodulation based on the support vector machine (SVM) classifier is introduced. The SVM method which selects only a few sampling points from the filter output was used for getting PPEs. The simulation results show that the accurate posterior probability can be obtained with this method and the BER performance can be improved significantly by applying LDPC codes. Moreover, we analyzed the effect of getting the posterior probability with different methods and different sampling rates. We show that there are more advantages of the SVM method under bad condition and it is less sensitive to the sampling rate than other methods. Thus, SVM is an effective method for EBPSK demodulation and getting posterior probability for LDPC decoding.


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