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Modelling Proteasome Dynamics in a Bayesian Framework

an existing computational model. In a second step, the author extends this model to be able to describe the influence of proteasome;

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Bayesian Methods for Nonlinear Classification and Regression

Classification and Regression is the first book to bring together, in a consistent statistical framework, the ideas of nonlinear modelling and Bayesian;

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Applied Bayesian Modelling

a broad and comprehensive account of applied Bayesian modelling. * Describes a variety of model assessment methods and the flexibility;

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Case Studies in Bayesian Statistical Modelling and Analysis

problem may be analysed using Bayesian methods. * Features approaches that can be used in a wide area of application, such as, health, the;

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Bayesian Thinking, Modeling and Computation

summarize inferences using simulation. The book covers wide range of topics including objective and subjective Bayesian inferences with a variety;

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Spatial Pattern Dynamics in Aquatic Ecosystem Modelling

patterns exhibited in GIS density maps. A synthesis modelling framework was developed to include biological/ecological growth and diffusive;

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Spatial Pattern Dynamics in Aquatic Ecosystem Modelling

patterns exhibited in GIS density maps. A synthesis modelling framework was developed to include biological/ecological growth and diffusive;

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An Introduction to Bayesian Inference, Methods and Computation

These lecture notes provide a rapid, accessible introduction to Bayesian statistical methods. The course covers the fundamental philosophy;

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A Unified Computational Fluid Dynamics Framework from Rarefied to Continuum Regimes

This Element presents a unified computational fluid dynamics framework from rarefied to continuum regimes. The framework is based on the;

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Handbook of Approximate Bayesian Computation

first time in a single volume, the Handbook of Approximate Bayesian Computation (ABC) presents an extensive overview of the theory, practice and;

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Bayesian Hierarchical Models

An intermediate-level treatment of Bayesian hierarchical models and their applications, this book demonstrates the advantages of a Bayesian;

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Bayesian Hierarchical Models

An intermediate-level treatment of Bayesian hierarchical models and their applications, this book demonstrates the advantages of a Bayesian;

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Bayesian Networks

provides a general introduction to Bayesian networks, defining and illustrating the basic concepts with pedagogical examples and twenty real-life;

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Towards Bayesian Model-Based Demography

framework based on the Bayesian statistical reasoning. Principles of uncertainty quantification are used to devise innovative computer-based;

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Towards Bayesian Model-Based Demography

framework based on the Bayesian statistical reasoning. Principles of uncertainty quantification are used to devise innovative computer-based;

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Dynamics and Bifurcations of Non-Smooth Mechanical Systems

This monograph combines the knowledge of both the field of nonlinear dynamics and non-smooth mechanics, presenting a framework for a class;

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Bayesian Analysis with Python

Unleash the power and flexibility of the Bayesian framework About This Book * Simplify the Bayes process for solving complex;

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Modelling Operational Risk Using Bayesian Inference

has developed a new regulatory framework for capital measurement and standards for the banking sector. This has formally defined operational;

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Unified Theories in Finance

This book provides a new framework for asset dynamics modelling. Known models are naturally parametrized and new models of increasing;

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Bayesian Statistics and Quality Modelling in the Agro-Food Production Chain

The food market is changing from a producer-controlled to a consumer-directed market. A main driving force is consumer concern about;

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Bayesian Statistical Modelling

Bayesian methods combine the evidence from the data at hand with previous quantitative knowledge to analyse practical problems in a wide;

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Bayesian Approach To Intrepreting Archaeological Data

and statistical modelling within the Bayesian framework, a variety of real case studies are presented covering areas of common interest to;

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Visual Analysis of Behaviour

This book presents a comprehensive treatment of visual analysis of behaviour from computational-modelling and algorithm-design perspectives;

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Bayesian Modeling and Computation in Python

Bayesian Modeling and Computation in Python aims to help beginner Bayesian practitioners to become intermediate modelers. It uses a hands;

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Data Analysis Using Hierarchical Generalized Linear Models with R

framework, and especially for those searching for a bridge between Bayesian and frequentist statistics.;

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Data Analysis Using Hierarchical Generalized Linear Models with R

framework, and especially for those searching for a bridge between Bayesian and frequentist statistics.;

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The Ubiquitin-proteasome System

to the discoverers of ubiquitin as a cofactor for intracellular non-lysosomal proteolysis. There is a voluminous literature showing that;

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