Bayesian Hierarchical Models in Characterizing Molecular Adaptation PDF Download
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Author: Sabeli Datta
Publisher:
ISBN:
Category :
Languages : en
Pages : 348
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Book Description
Author: Sabeli Datta
Publisher:
ISBN:
Category :
Languages : en
Pages : 348
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Book Description
Author: Raquel Prado
Publisher: CRC Press
ISBN: 1498747043
Category : Mathematics
Languages : en
Pages : 473
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Book Description
• Expanded on aspects of core model theory and methodology. • Multiple new examples and exercises. • Detailed development of dynamic factor models. • Updated discussion and connections with recent and current research frontiers.
Author: William F. Rosenberger
Publisher: John Wiley & Sons
ISBN: 1118742249
Category : Mathematics
Languages : en
Pages : 284
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Book Description
Praise for the First Edition “All medical statisticians involved in clinical trials should read this book...” - Controlled Clinical Trials Featuring a unique combination of the applied aspects of randomization in clinical trials with a nonparametric approach to inference, Randomization in Clinical Trials: Theory and Practice, Second Edition is the go-to guide for biostatisticians and pharmaceutical industry statisticians. Randomization in Clinical Trials: Theory and Practice, Second Edition features: Discussions on current philosophies, controversies, and new developments in the increasingly important role of randomization techniques in clinical trials A new chapter on covariate-adaptive randomization, including minimization techniques and inference New developments in restricted randomization and an increased focus on computation of randomization tests as opposed to the asymptotic theory of randomization tests Plenty of problem sets, theoretical exercises, and short computer simulations using SAS® to facilitate classroom teaching, simplify the mathematics, and ease readers’ understanding Randomization in Clinical Trials: Theory and Practice, Second Edition is an excellent reference for researchers as well as applied statisticians and biostatisticians. The Second Edition is also an ideal textbook for upper-undergraduate and graduate-level courses in biostatistics and applied statistics. William F. Rosenberger, PhD, is University Professor and Chairman of the Department of Statistics at George Mason University. He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics, and author of over 80 refereed journal articles, as well as The Theory of Response-Adaptive Randomization in Clinical Trials, also published by Wiley. John M. Lachin, ScD, is Research Professor in the Department of Epidemiology and Biostatistics as well as in the Department of Statistics at The George Washington University. A Fellow of the American Statistical Association and the Society for Clinical Trials, Dr. Lachin is actively involved in coordinating center activities for clinical trials of diabetes. He is the author of Biostatistical Methods: The Assessment of Relative Risks, Second Edition, also published by Wiley.
Author:
Publisher: ScholarlyEditions
ISBN: 1464921059
Category : Medical
Languages : en
Pages : 699
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Book Description
Advances in Biotechnology Research and Application: 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Biotechnology. The editors have built Advances in Biotechnology Research and Application: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Biotechnology in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Advances in Biotechnology Research and Application: 2011 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.
Author: Raquel Prado
Publisher: CRC Press
ISBN: 1420093363
Category : Mathematics
Languages : en
Pages : 375
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Book Description
Focusing on Bayesian approaches and computations using simulation-based methods for inference, Time Series: Modeling, Computation, and Inference integrates mainstream approaches for time series modeling with significant recent developments in methodology and applications of time series analysis. It encompasses a graduate-level account of Bayesian time series modeling and analysis, a broad range of references to state-of-the-art approaches to univariate and multivariate time series analysis, and emerging topics at research frontiers. The book presents overviews of several classes of models and related methodology for inference, statistical computation for model fitting and assessment, and forecasting. The authors also explore the connections between time- and frequency-domain approaches and develop various models and analyses using Bayesian tools, such as Markov chain Monte Carlo (MCMC) and sequential Monte Carlo (SMC) methods. They illustrate the models and methods with examples and case studies from a variety of fields, including signal processing, biomedicine, and finance. Data sets, R and MATLAB® code, and other material are available on the authors’ websites. Along with core models and methods, this text offers sophisticated tools for analyzing challenging time series problems. It also demonstrates the growth of time series analysis into new application areas.
Author: Kim-Anh Do
Publisher: Cambridge University Press
ISBN: 052186092X
Category : Mathematics
Languages : en
Pages : 437
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Book Description
Expert overviews of Bayesian methodology, tools and software for multi-platform high-throughput experimentation.
Author: Ziheng Yang
Publisher: Oxford University Press
ISBN: 0199602603
Category : Science
Languages : en
Pages : 509
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Book Description
Studies of evolution at the molecular level have experienced phenomenal growth in the last few decades, due to rapid accumulation of genetic sequence data, improved computer hardware and software, and the development of sophisticated analytical methods. The flood of genomic data has generated an acute need for powerful statistical methods and efficient computational algorithms to enable their effective analysis and interpretation. Molecular Evolution: a statistical approach presents and explains modern statistical methods and computational algorithms for the comparative analysis of genetic sequence data in the fields of molecular evolution, molecular phylogenetics, statistical phylogeography, and comparative genomics. Written by an expert in the field, the book emphasizes conceptual understanding rather than mathematical proofs. The text is enlivened with numerous examples of real data analysis and numerical calculations to illustrate the theory, in addition to the working problems at the end of each chapter. The coverage of maximum likelihood and Bayesian methods are in particular up-to-date, comprehensive, and authoritative. This advanced textbook is aimed at graduate level students and professional researchers (both empiricists and theoreticians) in the fields of bioinformatics and computational biology, statistical genomics, evolutionary biology, molecular systematics, and population genetics. It will also be of relevance and use to a wider audience of applied statisticians, mathematicians, and computer scientists working in computational biology.
Author: Ross D.E. MacPhee
Publisher: Springer Science & Business Media
ISBN: 1475752024
Category : Science
Languages : en
Pages : 402
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Book Description
"Near time" -an interval that spans the last 100,000 years or so of earth history-qualifies as a remarkable period for many reasons. From an anthropocentric point of view, the out standing feature of near time is the fact that the evolution, cultural diversification, and glob al spread of Homo sapiens have all occurred within it. From a wider biological perspective, however, the hallmark of near time is better conceived of as being one of enduring, repeat ed loss. The point is important. Despite the sense of uniqueness implicit in phrases like "the biodiversity crisis," meant to convey the notion that the present bout of extinctions is by far the worst endured in recent times, substantial losses have occurred throughout near time. In the majority of cases, these losses occurred when, and only when, people began to ex pand across areas that had never before experienced their presence. Although the explana tion for these correlations in time and space may seem obvious, it is one thing to rhetori cally observe that there is a connection between humans and recent extinctions, and quite another to demonstrate it scientifically. How should this be done? Traditionally, the study of past extinctions has fallen largely to researchers steeped in such disciplines as paleontology, systematics, and paleoecology. The evaluation of future losses, by contrast, has lain almost exclusively within the domain of conservation biolo gists. Now, more than ever, there is opportunity for overlap and sharing of information.
Author:
Publisher:
ISBN:
Category : Amino acid sequence
Languages : en
Pages : 132
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Book Description
Author: Alexei J. Drummond
Publisher: Cambridge University Press
ISBN: 1316298345
Category : Science
Languages : en
Pages : 263
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Book Description
What are the models used in phylogenetic analysis and what exactly is involved in Bayesian evolutionary analysis using Markov chain Monte Carlo (MCMC) methods? How can you choose and apply these models, which parameterisations and priors make sense, and how can you diagnose Bayesian MCMC when things go wrong? These are just a few of the questions answered in this comprehensive overview of Bayesian approaches to phylogenetics. This practical guide: • Addresses the theoretical aspects of the field • Advises on how to prepare and perform phylogenetic analysis • Helps with interpreting analyses and visualisation of phylogenies • Describes the software architecture • Helps developing BEAST 2.2 extensions to allow these models to be extended further. With an accompanying website providing example files and tutorials (http://beast2.org/), this one-stop reference to applying the latest phylogenetic models in BEAST 2 will provide essential guidance for all users – from those using phylogenetic tools, to computational biologists and Bayesian statisticians.
