Bayesian Analysis
نویسنده
چکیده
In the preceding paper, Bayesian analysis was applied to the parameter estimation problem, given quadrature NMR data. Here Bayesian analysis is extended to the problem of selecting the model which is most probable in view of the data and all the prior information. In addition to the analytic calculation, two examples are given. The rst example demonstrates how to use Bayesian probability theory to detect small signals in noise. The second example uses Bayesian probability theory to compute the probability of the number of decaying exponentials in simulated T 1 data. The Bayesian answer to this question is essentially a microcosm of the scientiic method and a quantitative statement of Ockham's razor: theorize about possible models, compare these to experiment; and select the simplest model that \best" ts the data.
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