Highly Structured Stochastic Systems

Highly Structured Stochastic Systems PDF Author: Ken Green
Publisher:
ISBN: 9780471499831
Category :
Languages : en
Pages : 450

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Book Description

Highly Structured Stochastic Systems

Highly Structured Stochastic Systems PDF Author: Ken Green
Publisher:
ISBN: 9780471499831
Category :
Languages : en
Pages : 450

Get Book Here

Book Description


Highly Structured Stochastic Systems

Highly Structured Stochastic Systems PDF Author: Peter J. Green
Publisher:
ISBN: 9780198510550
Category : Mathematics
Languages : en
Pages : 536

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Book Description
Through this text, the author aims to make recent developments in the title subject (a modern strategy for the creation of statistical models to solve 'real world' problems) accessible to graduate students and researchers in the field of statistics.

Handbook of Statistical Genetics

Handbook of Statistical Genetics PDF Author: David J. Balding
Publisher: John Wiley & Sons
ISBN: 9780470997628
Category : Science
Languages : en
Pages : 1616

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Book Description
The Handbook for Statistical Genetics is widely regarded as the reference work in the field. However, the field has developed considerably over the past three years. In particular the modeling of genetic networks has advanced considerably via the evolution of microarray analysis. As a consequence the 3rd edition of the handbook contains a much expanded section on Network Modeling, including 5 new chapters covering metabolic networks, graphical modeling and inference and simulation of pedigrees and genealogies. Other chapters new to the 3rd edition include Human Population Genetics, Genome-wide Association Studies, Family-based Association Studies, Pharmacogenetics, Epigenetics, Ethic and Insurance. As with the second Edition, the Handbook includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between the chapters, tying the different areas together. With heavy use of up-to-date examples, real-life case studies and references to web-based resources, this continues to be must-have reference in a vital area of research. Edited by the leading international authorities in the field. David Balding - Department of Epidemiology & Public Health, Imperial College An advisor for our Probability & Statistics series, Professor Balding is also a previous Wiley author, having written Weight-of-Evidence for Forensic DNA Profiles, as well as having edited the two previous editions of HSG. With over 20 years teaching experience, he’s also had dozens of articles published in numerous international journals. Martin Bishop – Head of the Bioinformatics Division at the HGMP Resource Centre As well as the first two editions of HSG, Dr Bishop has edited a number of introductory books on the application of informatics to molecular biology and genetics. He is the Associate Editor of the journal Bioinformatics and Managing Editor of Briefings in Bioinformatics. Chris Cannings – Division of Genomic Medicine, University of Sheffield With over 40 years teaching in the area, Professor Cannings has published over 100 papers and is on the editorial board of many related journals. Co-editor of the two previous editions of HSG, he also authored a book on this topic.

Fundamentals of the Theory of Structured Dependence between Stochastic Processes

Fundamentals of the Theory of Structured Dependence between Stochastic Processes PDF Author: Tomasz R. Bielecki
Publisher: Cambridge University Press
ISBN: 1107154251
Category : Business & Economics
Languages : en
Pages : 279

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Book Description
Comprehensive presentation of the technical aspects and applications of the theory of structured dependence between random processes.

Causality

Causality PDF Author: Carlo Berzuini
Publisher: John Wiley & Sons
ISBN: 1119941733
Category : Mathematics
Languages : en
Pages : 387

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Book Description
A state of the art volume on statistical causality Causality: Statistical Perspectives and Applications presents a wide-ranging collection of seminal contributions by renowned experts in the field, providing a thorough treatment of all aspects of statistical causality. It covers the various formalisms in current use, methods for applying them to specific problems, and the special requirements of a range of examples from medicine, biology and economics to political science. This book: Provides a clear account and comparison of formal languages, concepts and models for statistical causality. Addresses examples from medicine, biology, economics and political science to aid the reader's understanding. Is authored by leading experts in their field. Is written in an accessible style. Postgraduates, professional statisticians and researchers in academia and industry will benefit from this book.

Confidence, Likelihood, Probability

Confidence, Likelihood, Probability PDF Author: Tore Schweder
Publisher: Cambridge University Press
ISBN: 1316445054
Category : Mathematics
Languages : en
Pages : 521

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Book Description
This lively book lays out a methodology of confidence distributions and puts them through their paces. Among other merits, they lead to optimal combinations of confidence from different sources of information, and they can make complex models amenable to objective and indeed prior-free analysis for less subjectively inclined statisticians. The generous mixture of theory, illustrations, applications and exercises is suitable for statisticians at all levels of experience, as well as for data-oriented scientists. Some confidence distributions are less dispersed than their competitors. This concept leads to a theory of risk functions and comparisons for distributions of confidence. Neyman–Pearson type theorems leading to optimal confidence are developed and richly illustrated. Exact and optimal confidence distribution is the gold standard for inferred epistemic distributions. Confidence distributions and likelihood functions are intertwined, allowing prior distributions to be made part of the likelihood. Meta-analysis in likelihood terms is developed and taken beyond traditional methods, suiting it in particular to combining information across diverse data sources.

Coordinated Activity in the Brain

Coordinated Activity in the Brain PDF Author: Jose Luis Perez Velazquez
Publisher: Springer Science & Business Media
ISBN: 0387937978
Category : Medical
Languages : en
Pages : 285

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Book Description
Increasing interest in the study of coordinated activity of brain cell ensembles reflects the current conceptualization of brain information processing and cognition. It is thought that cognitive processes involve not only serial stages of sensory signal processing, but also massive parallel information processing circuitries, and therefore it is the coordinated activity of neuronal networks of brains that give rise to cognition and consciousness in general. While the concepts and techniques to measure synchronization are relatively well characterized and developed in the mathematics and physics community, the measurement of coordinated activity derived from brain signals is not a trivial task, and is currently a subject of debate. Coordinated Activity in the Brain: Measurements and Relevance to Brain Function and Behavior addresses conceptual and methodological limitations, as well as advantages, in the assessment of cellular coordinated activity from neurophysiological recordings. The book offers a broad overview of the field for investigators working in a variety of disciplines (neuroscience, biophysics, mathematics, physics, neurology, neurosurgery, psychology, biomedical engineering, computer science/computational biology), and introduces future trends for understanding brain activity and its relation to cognition and pathologies. This work will be valuable to professional investigators and clinicians, graduate and post-graduate students in related fields of neuroscience and biophysics, and to anyone interested in signal analysis techniques for studying brain function.

Handbook of Spatial Epidemiology

Handbook of Spatial Epidemiology PDF Author: Andrew B. Lawson
Publisher: CRC Press
ISBN: 148225302X
Category : Mathematics
Languages : en
Pages : 704

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Book Description
Handbook of Spatial Epidemiology explains how to model epidemiological problems and improve inference about disease etiology from a geographical perspective. Top epidemiologists, geographers, and statisticians share interdisciplinary viewpoints on analyzing spatial data and space-time variations in disease incidences. These analyses can provide imp

Analysis of Large and Complex Data

Analysis of Large and Complex Data PDF Author: Adalbert F.X. Wilhelm
Publisher: Springer
ISBN: 3319252267
Category : Computers
Languages : en
Pages : 640

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Book Description
This book offers a snapshot of the state-of-the-art in classification at the interface between statistics, computer science and application fields. The contributions span a broad spectrum, from theoretical developments to practical applications; they all share a strong computational component. The topics addressed are from the following fields: Statistics and Data Analysis; Machine Learning and Knowledge Discovery; Data Analysis in Marketing; Data Analysis in Finance and Economics; Data Analysis in Medicine and the Life Sciences; Data Analysis in the Social, Behavioural, and Health Care Sciences; Data Analysis in Interdisciplinary Domains; Classification and Subject Indexing in Library and Information Science. The book presents selected papers from the Second European Conference on Data Analysis, held at Jacobs University Bremen in July 2014. This conference unites diverse researchers in the pursuit of a common topic, creating truly unique synergies in the process.

Emerging Paradigms in Machine Learning

Emerging Paradigms in Machine Learning PDF Author: Sheela Ramanna
Publisher: Springer Science & Business Media
ISBN: 3642286992
Category : Technology & Engineering
Languages : en
Pages : 507

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Book Description
This book presents fundamental topics and algorithms that form the core of machine learning (ML) research, as well as emerging paradigms in intelligent system design. The multidisciplinary nature of machine learning makes it a very fascinating and popular area for research. The book is aiming at students, practitioners and researchers and captures the diversity and richness of the field of machine learning and intelligent systems. Several chapters are devoted to computational learning models such as granular computing, rough sets and fuzzy sets An account of applications of well-known learning methods in biometrics, computational stylistics, multi-agent systems, spam classification including an extremely well-written survey on Bayesian networks shed light on the strengths and weaknesses of the methods. Practical studies yielding insight into challenging problems such as learning from incomplete and imbalanced data, pattern recognition of stochastic episodic events and on-line mining of non-stationary data streams are a key part of this book.