model based inference in the life sciences

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Model Based Inference In The Life Sciences

Author : David R. Anderson
ISBN : 0387740759
Genre : Science
File Size : 90. 48 MB
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This textbook introduces a science philosophy called "information theoretic" based on Kullback-Leibler information theory. It focuses on a science philosophy based on "multiple working hypotheses" and statistical models to represent them. The text is written for people new to the information-theoretic approaches to statistical inference, whether graduate students, post-docs, or professionals. Readers are however expected to have a background in general statistical principles, regression analysis, and some exposure to likelihood methods. This is not an elementary text as it assumes reasonable competence in modeling and parameter estimation.

Mri In Psychiatry

Author : Christoph Mulert
ISBN : 9783642545429
Genre : Medical
File Size : 26. 87 MB
Format : PDF, ePub
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This is the first comprehensive textbook on the use of MRI in psychiatry covering imaging techniques, brain systems and a review of findings in different psychiatric disorders. The book is divided into three sections, the first of which covers in detail all the major MRI-based methodological approaches available today, including fMRI, EEG-fMRI, DTI and MR spectroscopy. In addition, the role of MRI in imaging genetics and combined brain stimulation and imaging is carefully explained. The second section provides an overview of the different brain systems that are relevant for psychiatric disorders, including the systems for perception, emotion, cognition and reward. The final part of the book presents the MRI findings that are obtained in all the major psychiatric disorders using the previously discussed techniques. Numerous carefully chosen images support the informative text, making this an ideal reference work for all practitioners and trainees with an interest in this flourishing field.

Mathematics And Life Sciences

Author : Alexandra V. Antoniouk
ISBN : 9783110288537
Genre : Mathematics
File Size : 80. 12 MB
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The book provides a unique collection of in-depth mathematical, statistical, and modeling methods and techniques for life sciences, as well as their applications in a number of areas within life sciences. It also includes a range of new ideas that represent emerging frontiers in life sciences where the application of such quantitative methods and techniques is becoming increasingly important. The book is aimed at researchers in academia, practitioners and graduate students who want to foster interdisciplinary collaborations required to meet the challenges at the interface of modern life sciences and mathematics.

Issues In Life Sciences Molecular Biology 2011 Edition

Author :
ISBN : 9781464963483
Genre : Science
File Size : 48. 46 MB
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Issues in Life Sciences: Molecular Biology / 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Life Sciences—Molecular Biology. The editors have built Issues in Life Sciences: Molecular Biology: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Life Sciences—Molecular Biology 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 Issues in Life Sciences: Molecular Biology: 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/.

Springer Handbook Of Model Based Science

Author : Lorenzo Magnani
ISBN : 9783319305264
Genre : Computers
File Size : 48. 92 MB
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This handbook offers the first comprehensive reference guide to the interdisciplinary field of model-based reasoning. It highlights the role of models as mediators between theory and experimentation, and as educational devices, as well as their relevance in testing hypotheses and explanatory functions. The Springer Handbook merges philosophical, cognitive and epistemological perspectives on models with the more practical needs related to the application of this tool across various disciplines and practices. The result is a unique, reliable source of information that guides readers toward an understanding of different aspects of model-based science, such as the theoretical and cognitive nature of models, as well as their practical and logical aspects. The inferential role of models in hypothetical reasoning, abduction and creativity once they are constructed, adopted, and manipulated for different scientific and technological purposes is also discussed. Written by a group of internationally renowned experts in philosophy, the history of science, general epistemology, mathematics, cognitive and computer science, physics and life sciences, as well as engineering, architecture, and economics, this Handbook uses numerous diagrams, schemes and other visual representations to promote a better understanding of the concepts. This also makes it highly accessible to an audience of scholars and students with different scientific backgrounds. All in all, the Springer Handbook of Model-Based Science represents the definitive application-oriented reference guide to the interdisciplinary field of model-based reasoning.

When To Use What Research Design

Author : W. Paul Vogt
ISBN : 9781462503605
Genre : Social Science
File Size : 23. 15 MB
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Systematic, practical, and accessible, this is the first book to focus on finding the most defensible design for a particular research question. Thoughtful guidelines are provided for weighing the advantages and disadvantages of various methods, including qualitative, quantitative, and mixed methods designs. The book can be read sequentially or readers can dip into chapters on specific stages of research (basic design choices, selecting and sampling participants, addressing ethical issues) or data collection methods (surveys, interviews, experiments, observations, archival studies, and combined methods). Many chapter headings and subheadings are written as questions, helping readers quickly find the answers they need to make informed choices that will affect the later analysis and interpretation of their data. Useful features include: *Easy-to-navigate part and chapter structure. *Engaging research examples from a variety of fields. *End-of-chapter tables that summarize the main points covered. *Detailed suggestions for further reading at the end of each chapter. *Integration of data collection, sampling, and research ethics in one volume. *Comprehensive glossary.

Principles Of Statistical Inference

Author : D. R. Cox
ISBN : 1139459139
Genre : Mathematics
File Size : 45. 13 MB
Format : PDF, Kindle
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In this definitive book, D. R. Cox gives a comprehensive and balanced appraisal of statistical inference. He develops the key concepts, describing and comparing the main ideas and controversies over foundational issues that have been keenly argued for more than two-hundred years. Continuing a sixty-year career of major contributions to statistical thought, no one is better placed to give this much-needed account of the field. An appendix gives a more personal assessment of the merits of different ideas. The content ranges from the traditional to the contemporary. While specific applications are not treated, the book is strongly motivated by applications across the sciences and associated technologies. The mathematics is kept as elementary as feasible, though previous knowledge of statistics is assumed. The book will be valued by every user or student of statistics who is serious about understanding the uncertainty inherent in conclusions from statistical analyses.

Biometrika

Author : D. M. Titterington
ISBN : 0198509936
Genre : Mathematics
File Size : 78. 75 MB
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The book celebrates the centenary of Biometrika, one of the world's leading academic journals in statistical theory and methodology by collating two sets of papers from the journal. One set consists of seven articles that review the journal's contribution to statistical science; the other set contains ten seminal papers from the journals first hundred years. The book opens with an introduction by the editors Professor D.M. Titterington and Sir David Cox.

Hierarchical Modeling And Inference In Ecology

Author : J. Andrew Royle
ISBN : 9780080559254
Genre : Science
File Size : 90. 57 MB
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A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures. The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution * abundance models based on many sampling protocols, including distance sampling * capture-recapture models with individual effects * spatial capture-recapture models based on camera trapping and related methods * population and metapopulation dynamic models * models of biodiversity, community structure and dynamics * Wide variety of examples involving many taxa (birds, amphibians, mammals, insects, plants) * Development of classical, likelihood-based procedures for inference, as well as Bayesian methods of analysis * Detailed explanations describing the implementation of hierarchical models using freely available software such as R and WinBUGS * Computing support in technical appendices in an online companion web site

Model Selection And Multimodel Inference

Author : Kenneth P. Burnham
ISBN : 9780387224565
Genre : Mathematics
File Size : 34. 6 MB
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A unique and comprehensive text on the philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. It contains several new approaches to estimating model selection uncertainty and incorporating selection uncertainty into estimates of precision. An array of examples is given to illustrate various technical issues. The text has been written for biologists and statisticians using models for making inferences from empirical data.

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