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Bayesian inference has become a standard method of analysis in many fields of science. Students and researchers in experimental psychology;
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Bayesian inference has become a standard method of analysis in many fields of science. Students and researchers in experimental psychology;
Vergelijkbare producten zoals Bayesian Cognitive Modeling
This book presents a flexible Bayesian framework for combining neural and cognitive models. Traditionally, studies in cognition and;
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; convergent methods of memory research; theories for discriminating signal from noise; bayesian cognitive modeling; mathematical modeling in cognition;
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A hands-on introduction to the principles of Bayesian modeling using WinBUGS Bayesian Modeling Using WinBUGS provides an easily accessible;
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learning, unsupervised learning, and Bayesian models; and models of social interaction. All mathematical concepts are introduced gradually, with no;
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This accessible reference includes selected contributions from Bayesian Thinking - Modeling and Computation, Volume 25 in the Handbook;
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Making statistical modeling and inference more accessible to ecologists and related scientists, Introduction to Hierarchical Bayesian;
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Making statistical modeling and inference more accessible to ecologists and related scientists, Introduction to Hierarchical Bayesian;
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Bayesian Modeling in Bioinformatics discusses the development and application of Bayesian statistical methods for the analysis of high;
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Bayesian Modeling in Bioinformatics discusses the development and application of Bayesian statistical methods for the analysis of high;
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Focusing on data commonly found in public health databases and clinical settings, Bayesian Disease Mapping: Hierarchical Modeling;
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Bayesian Methods in Finance provides a detailed overview of the theory of Bayesian methods and explains their real-world applications to;
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statistical methods for - timating model parameters and evaluating model t. However, the Bayesian methodology has shown great potential, particularly;
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problems, and the Bayesian paradigm has a major role to play in the understanding of the complex interplay of context and individual predisposition;
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For the development of clinical decision support systems based on Bayesian networks, Mario A. Cypko investigates comprehensive expert;
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cognitive maps, testing strategies of hypothesis, maximum likelihood estimator, Bayesian statistics, and discrete probability models of neural;
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Along with many practical applications, Bayesian Model Selection and Statistical Modeling presents an array of Bayesian inference and model;
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This book explains the foundation of approximate Bayesian computation (ABC), an approach to Bayesian inference that does not require the;
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of evolution took place in the late 1990s or early 2000s, when full-fledged Bayesian machinery was introduced to NLP. This Bayesian approach to NLP has;
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Ando shows how to implement a variety of Bayesian inference using R and sampling methods, such as Markov chain Monte Carlo. He covers the;
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Broadening its scope to nonstatisticians, Bayesian Methods for Data Analysis, Third Edition provides an accessible introduction to the;
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Flexible Bayesian Regression Modeling is a step-by-step guide to the Bayesian revolution in regression modeling, for use in advanced;
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Since the publication of the second edition, many new Bayesian tools and methods have been developed for space-time data analysis, the;
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Since the publication of the second edition, many new Bayesian tools and methods have been developed for space-time data analysis, the;
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financial investments to email filtering, are incomplete or uncertain in nature. Probability theory and Bayesian computing together provide an;
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