Advances In The Theory And Practice Of Statistics
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Statistics in Theory and Practice
Author: Robert Lupton
language: en
Publisher: Princeton University Press
Release Date: 1993-08
Aimed at readers without a specialist scientific background, this monograph describes the theory underlying classical statistical methods. Readers with some familiarity of the standard tests will learn more about their strengths, weaknesses and domains of applicability.
Advances in the Theory and Practice of Smart Specialization
Regional growth in the European Union hinges to a large extent on smart specialization, a new and exciting theme in economic innovation studies. Advances in the Theory and Practice of Smart Specialization illuminates problems that have stifled the implementation of smart specialization policies, such as unique regional constraints and the inter-dependent demands of economic growth and commercial development. Forward-looking and pragmatic, it provides guidance for developing smart specialization strategies both to those involved in European affairs and others grappling with regional innovation and economic development worldwide. - Emphasizes specific contexts for smart specialization, its international approach and institutional preconditions - Examines comparable initiatives worldwide - Explains how to implement smart specialization policies given different development levels of regions and countries
Advanced Mean Field Methods
This book covers the theoretical foundations of advanced mean field methods, explores the relation between the different approaches, examines the quality of the approximation obtained, and demonstrates their application to various areas of probabilistic modeling. A major problem in modern probabilistic modeling is the huge computational complexity involved in typical calculations with multivariate probability distributions when the number of random variables is large. Because exact computations are infeasible in such cases and Monte Carlo sampling techniques may reach their limits, there is a need for methods that allow for efficient approximate computations. One of the simplest approximations is based on the mean field method, which has a long history in statistical physics. The method is widely used, particularly in the growing field of graphical models. Researchers from disciplines such as statistical physics, computer science, and mathematical statistics are studying ways to improve this and related methods and are exploring novel application areas. Leading approaches include the variational approach, which goes beyond factorizable distributions to achieve systematic improvements; the TAP (Thouless-Anderson-Palmer) approach, which incorporates correlations by including effective reaction terms in the mean field theory; and the more general methods of graphical models. Bringing together ideas and techniques from these diverse disciplines, this book covers the theoretical foundations of advanced mean field methods, explores the relation between the different approaches, examines the quality of the approximation obtained, and demonstrates their application to various areas of probabilistic modeling.