Chebyshev methods in numerical approximation by Martin Avery Snyder

By Martin Avery Snyder

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Another problem centers on the quality and extent of the prior beliefs used in BN inference. A BN is only as useful as the reliability of this prior knowledge, namely, network parameters of prior beliefs of leaf nodes. Either an excessively optimistic or pessimistic expectation of the quality of these prior beliefs will distort the entire network and invalidate the results (Niedermayer, 1998). 3. Hybrid and Hierarchal BNs with HMMs In this section, we will consider the fusion of these two probabilistic models.

Together, these two dimensions of Q/CSS—pure versus applied, and substantive versus methodological—readily suggest four areas or clusters of computational social science investigations. One dimension contains instances of Q/CSS that are primarily focused on the role of information and computation in human societies—for example, how a system of government functions (and fails) based on information processing, human choices, and resource flows. Another dimension contains Q/CSS that offer a computational perspective on human and social phenomena highlighting certain entities, properties, and dynamics of the social universe—namely, information processing and adaptation in complex environments—while minimizing others.

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