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Foundations of Info-Metrics - Modeling, Inference, and Imperfect Information (Paperback)
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Foundations of Info-Metrics - Modeling, Inference, and Imperfect Information (Paperback)
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Info-metrics is the science of modeling, reasoning, and drawing
inferences under conditions of noisy and insufficient information.
It is at the intersection of information theory, statistical
inference, and decision-making under uncertainty. It plays an
important role in helping make informed decisions even when there
is inadequate or incomplete information because it provides a
framework to process available information with minimal reliance on
assumptions that cannot be validated. In this pioneering book, Amos
Golan, a leader in info-metrics, focuses on unifying information
processing, modeling and inference within a single constrained
optimization framework. Foundations of Info-Metrics provides an
overview of modeling and inference, rather than a problem specific
model, and progresses from the simple premise that information is
often insufficient to provide a unique answer for decisions we wish
to make. Each decision, or solution, is derived from the available
input information along with a choice of inferential procedure. The
book contains numerous multidisciplinary applications and case
studies, which demonstrate the simplicity and generality of the
framework in real world settings. Examples include initial
diagnosis at an emergency room, optimal dose decisions, election
forecasting, network and information aggregation, weather pattern
analyses, portfolio allocation, strategy inference for interacting
entities, incorporation of prior information, option pricing, and
modeling an interacting social system. Graphical representations
illustrate how results can be visualized while exercises and
problem sets facilitate extensions. This book is this designed to
be accessible for researchers, graduate students, and practitioners
across the disciplines.
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