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The aim of Bayesian statistics is typically to characterize the posterior probability distribution of a set of hypotheses, given a body of data, a probabilistic model for the generation of that data, and an explicit probabilistic description of prior beliefs.
See Additional file 1 for details for implementation particulars and description of prior distributions of parameters, and see Additional file 2 for the WinBUGS code.
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A detailed description of priors used can be accessed in the Appendix S2.
According to the description in of Prior distribution section of this paper, we placed hierarchical uniform priors on Se 1 and on Se 2. These hierarchical priors were elicited based on the opinions of a co-author (Dr. Hao Yu) and on published papers [ 2, 30].
Prior to any experimental observation, these distributions are estimated based solely on our subjective assessments (assuming that little is known about the network topology a priori) and are referred to as prior distributions (see the 'Methods' section for a detailed description of the prior distributions of the unknown variables A i j, r i j, ∊ i k ).
In a recent legal case, for instance, the description of a prior invention posted on a precursor of today's Internet forums was deemed sufficient to invalidate some patent claims.
To analyze experiments 1 and 2 with our Bayesian approach we need to propose probabilistic description of the prior's mean and variance.
This paper describes the development and content of these two DAs, including a description of our prior feasibility studies and randomized trials, each of which contributed to the evolution of these tools.
Clayton affirms creation from nothing as a description of creaturely existence prior to God's decision.
For description of the three prior knowledge sources see Methods.
Description of treatment given prior to inclusion in the study is given in Table 1.
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