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Simplicity, Inference and Modelling

including philosophers, mathematicians, econometricians and economists, this 2002 monograph examines simplicity by asking six questions: what;

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Simplicity, Inference and Modelling

including philosophers, mathematicians, econometricians and economists, this 2002 monograph examines simplicity by asking six questions: what;

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Statistical Foundations of Econometric Modelling

This textbook provides an introduction to econometrics through a grounding in probability theory and statistical inference. The emphasis;

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Statistical Inference for Fractional Diffusion Processes

Stochastic processes are widely used for model building in the social, physical, engineering and life sciences as well as in financial;

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An Introduction to Bayesian Inference, Methods and Computation

and principles of Bayesian inference, including the reasoning behind the prior/likelihood model construction synonymous with Bayesian methods;

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Reconstructing the Past

of hypothesis testing and theory evaluation that run head on into long standing issues concerning simplicity/parsimony in the philosophy of science;

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Inference for Diffusion Processes

natural sciences but also in finance and economics. Their mathematical theory, however, is challenging, and hence diffusion modelling is often;

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Statistical Modelling and Analysis Techniques

Statistical Modelling and Analysis Techniques provides insights into modelling and analytic aspects of random events and discusses;

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Computational Systems Biology

Computational Systems Biology: Inference and Modelling provides an introduction to, and overview of, network analysis inference approaches;

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Probability Theory and Statistical Inference

This major textbook from a distinguished econometrician is intended for students taking introductory courses in probability theory and;

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Probability and Statistical Inference

Probability and Statistical Inference: From Basic Principles to Advanced Models covers aspects of probability, distribution theory, and;

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Probability and Statistical Inference

Probability and Statistical Inference: From Basic Principles to Advanced Models covers aspects of probability, distribution theory, and;

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Simplicity, Complexity and Modelling

models, as to how to combine results from different models and how to propagate model uncertainty into forecasts. This book represents the result;

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Stochastic Modelling for Systems Biology, Third Edition

methods and applications are included in the book, and the use of R for practical illustration of the algorithms has been greatly extended. There;

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Stochastic Modelling for Systems Biology, Third Edition

methods and applications are included in the book, and the use of R for practical illustration of the algorithms has been greatly extended. There;

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Stochastic Modelling For Systems Biology

Although stochastic kinetic models are increasingly accepted as the best way to represent and simulate genetic and biochemical networks;

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Dynamical Systems and Ergodic Theory at Saint-Flour

natural sciences but also in finance and economics. Their mathematical theory, however, is challenging, and hence diffusion modelling is often;

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Modelling for Coastal Hydraulics and Engineering

, involve certain assumptions and limitations, and can be manipulated only by experienced engineers who have a thorough understanding of the;

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Modelling for Coastal Hydraulics and Engineering

, involve certain assumptions and limitations, and can be manipulated only by experienced engineers who have a thorough understanding of the;

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Machine Learning for Knowledge Discovery with R

Machine Learning for Knowledge Discovery with R contains methodologies and examples for statistical modelling, inference, and prediction;

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Probability Theory Vol 1

imaginary distinction between 'probability theory' and 'statistical inference', leaving a logical unity and simplicity, which provides greater;

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Multi-State Survival Models for Interval-Censored Data

between states over time. It is targeted at researchers in medical statistics, epidemiology, demography, and social statistics. One of the;

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Multi-State Survival Models for Interval-Censored Data

between states over time. It is targeted at researchers in medical statistics, epidemiology, demography, and social statistics. One of the;

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In All Likelihood

unifying the demands of statistical modelling and the theory of inference. Every likelihood concept is illustrated by realistic examples, which are;

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Models Of The Ecological Hierarchy

In the application of statistics to ecological inference problems, hierarchical models combine e;...

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Modelling the Probability Distribution of Stock Price Changes

The book is a survey of major probability models of interest to academics and practitioners working in finance modelling. The book borrows;

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Pathwise Estimation and Inference for Diffusion Market Models

Pathwise estimation and inference for diffusion market models discusses contemporary techniques for inferring, from options and bond prices;

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