Detection Bayesian

The authors also evaluated the performance of various DES-T and DES cutoffs for detecting taxon members defined by Bayesian probabilities. Waller and Ross found that DES-T cutoffs work much better than the cutoffs on the DES because they have higher sensitivity, specificity, and positive and negative predictive values. One could say that the authors stacked the deck in favor of the DES-T, as the Bayesian probabilities and DES-T scores are based on the same data. However, this redundancy is unavoidable, since there is no other method of assessing taxon membership. It is important to evaluate the qualities of DES-T cutoffs for studies that will use the DES-T, rather than the Bayesian scoring scheme. 

Mckeigue, P.M., Carpenter, J., Parra, E.J., and Shriver, M.D. (2000) Estimation of admixture and detection of linkage in admixed populations by a Bayesian approach application to African-American populations. Ann. Hum. Genet. 64, 171-186. 

Stegle O et at (2010) A robust Bayesian two-sample test for detecting intervals of differential gene expression in microarray time series. J Comput Biol 17 355-367. doi 10.1089/ cmb.2009.0175... 

Godsill and Rayner, 1992] Godsill, S. J. and Rayner, P. J. W. (1992). A Bayesian approach to the detection and correction of bursts of errors in audio signals. In Proc. IEEE Int. Conf. Acoust., Speech and Signal Proc, volume 2, pages 261-264, San Francisco, CA. 

Click detection within a Bayesian framework has introduced the concept of an explicit model for the corrupting noise process through the noise density pvu h Effective... 

Bayesian probability theory157 can also be applied to the problem of NMR parameter estimation this approach incorporates prior knowledge of the NMR parameters and is particularly useful at short aquisition times158 and when the FID contains few data points.159 Bayesian analysis gives more precise estimates of the NMR parameters than do methods based on the discrete Fourier transform (DFT).160 The amplitudes can be estimated independently of the phase, frequency and decay constants of the resonances.161 For the usual method of quadrature detection, it is appropriate to apply this technique to the two quadrature signals in the time domain.162-164... 

For example, if k decays or a rare short-lived nuclide were detected in the course of a long bombardment and we need to know the Bayesian confidence interval for the yield rate (per the duration of the bombardment) 0, then L(k ) is the Poisson distribution ... 

It has recently become more widely appreciated that the presence of rotational diffusional anisotropy in proteins and other macromolecules can have a significant affect on the interpretation of NMR relaxation data in terms of molecular motion. Andrec et al. showed how commonly used NMR relaxation data (Ti, T2 and NOE) obtained at two spectrometer frequencies can be analyzed using a Bayesian statistical approach to reliably detect and... 

A true PPC requires sampling from the posterior distribution of the fixed and random effects in the model, which is typically not known. A complete solution then usually requires Markov Chain Monte Carlo simulation, which is not easy to implement. Luckily for the analyst, Yano, Sheiner, and Beal (2001) showed that complete implementation of the algorithm does not appear to be necessary since fixing the values of the model parameters to their final values obtained using maximum likelihood resulted in PPC distributions that were as good as the full-blown Bayesian PPC distributions. In other words, using a predictive check resulted in distributions that were similar to PPC distributions. Unfortunately they also showed that the PPC is very conservative and not very powerful at detecting model misspecification. 

D. A. Winkler, F. Burden, Toxicity Modelling Using Bayesian Neural Nets and Automatic Relevance Detection. 

After a first paper in 1988, " Bretthorst paved the way for the application of Bayesian probability theory (BPT) in a series of three papers.- The first presents the connection between the theory and the case of NMR phenomena and discusses parameter estimation and detection of quadrature signals. The second " shows the ability of Bayesian methods to measure the quality of a model. The third " provides examples of applications to experimental data where decaying sinusoids are assumed. A fourth paper, produced during the following two years, discusses computer time requirements and noise, and it is shown to be important to include knowledge in the analysis," " while a fifth publication is devoted to amplitude estimations for multiplets of well-separated resonances. 

Finally, it should be noted that Bayesian methods are also used in NQR spectroscopy for the detection of landmines. ... 

From the classical perspective, the decision maker is concerned with determining the likelihood that a hypothesis is true. Bayesian inference is the best-known technique, but signal detection theory, and fundamentally different approaches such as the Dempster-Schafer method, have seen application. Each of these approaches is discussed below. 

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