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Science --- Reasoning --- Bayesian statistical decision theory
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This book is a collection of introductory, interdisciplinary articles and lectures covering the fundamentals of the maximum entropy approach, a powerful new technique that provides a much needed extension of the established principles of rational inference in the sciences. Maximum entropy allows the interpretation of incomplete and "noisy" data, providing a description of the underlying physical systems. It has found application in both practical and theoretical studies ranging from image enhancement to nuclear physics, and from statistical mechanics to economics. The work explores these applications with specific problems of data analysis taken from the physical sciences. It will interest all physical scientists who deal with data and its interpretation, including statisticians and statistical physicists.
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Artificial intelligence. --- Evidence. --- Bayesian statistical decision theory. --- Intelligence artificielle. --- Évidence. --- Statistique bayésienne. --- Évidence. --- Statistique bayésienne.
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Mathematical statistics --- Experimental design --- Estimation theory --- Bayesian statistical decision theory --- Regression Analysis --- 519.233 --- Bayesian statistical decision theory. --- Regression analysis --- #WWIS:d.d. Prof. Teugels --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Design of experiments --- Statistical design --- Mathematical optimization --- Research --- Science --- Statistical decision --- Statistics --- Analysis of means --- Analysis of variance --- Estimating techniques --- Least squares --- Stochastic processes --- Bayes' solution --- Bayesian analysis --- Parametric methods --- Experiments --- Methodology --- 519.233 Parametric methods
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