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Model Selection And Multimodel Inference
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Book Synopsis Model Selection and Multimodel Inference by : Kenneth P. Burnham
Download or read book Model Selection and Multimodel Inference written by Kenneth P. Burnham and published by Springer Science & Business Media. This book was released on 2007-05-28 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Model Selection and Multimodel Inference by : Kenneth P. Burnham
Download or read book Model Selection and Multimodel Inference written by Kenneth P. Burnham and published by Springer Science & Business Media. This book was released on 2003-12-04 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Model Selection and Inference by : Kenneth P. Burnham
Download or read book Model Selection and Inference written by Kenneth P. Burnham and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statisticians and applied scientists must often select a model to fit empirical data. This book discusses the philosophy and strategy of selecting such a model using the information theory approach pioneered by Hirotugu Akaike. This approach focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. The book includes practical applications in biology and environmental science.
Book Synopsis Model Selection and Multimodel Inference by : Kenneth P. Burnham
Download or read book Model Selection and Multimodel Inference written by Kenneth P. Burnham and published by . This book was released on 2014-01-15 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Spencers of Amberson Avenue by : Ethel Spencer
Download or read book The Spencers of Amberson Avenue written by Ethel Spencer and published by University of Pittsburgh Press. This book was released on 2010-09-24 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: This appealing memoir introduces the family of Charles Hart Spencer and his wife Mary Acheson: seven children born between 1884 and 1895. It also introduces a large Victorian house in Shadyside (a Pittsburgh neighborhood) and a middle-class way of life at the turn of the century. Mr. Spencer, who worked--not very happily--for Henry Clay Frick, was one of the growing number of middle-management employees in American industrial cities in the 1880s and 1890s. His income, which supported his family of nine, a cook, two regular nurses, and at times a wet nurse and her baby, guaranteed a comfortable life but not a luxurious one. In the words of the editors, the Spencers represent a class that "too often stands silent or stereotyped as we rush forward toward the greater glamour of the robber barons or their immigrant workers." Through the eyes of Ethel Spencer, the third daughter, we are led with warmth and humor through the routine of everyday life in this household: school, play, church on Sundays, illness, family celebrations, and vacations. Ethel was an observant child, with little sentimentality, and she wrote her memoir in later life as a professor of English with a gift for clear prose and the instincts of an anthropologist. As the editors observe, her memoir is "a fascinating insight into one kind of urban life of three generations ago."
Book Synopsis Model Based Inference in the Life Sciences by : David R. Anderson
Download or read book Model Based Inference in the Life Sciences written by David R. Anderson and published by Springer Science & Business Media. This book was released on 2007-12-22 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan by : Franzi Korner-Nievergelt
Download or read book Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan written by Franzi Korner-Nievergelt and published by Academic Press. This book was released on 2015-04-04 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN examines the Bayesian and frequentist methods of conducting data analyses. The book provides the theoretical background in an easy-to-understand approach, encouraging readers to examine the processes that generated their data. Including discussions of model selection, model checking, and multi-model inference, the book also uses effect plots that allow a natural interpretation of data. Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN introduces Bayesian software, using R for the simple modes, and flexible Bayesian software (BUGS and Stan) for the more complicated ones. Guiding the ready from easy toward more complex (real) data analyses ina step-by-step manner, the book presents problems and solutions—including all R codes—that are most often applicable to other data and questions, making it an invaluable resource for analyzing a variety of data types. Introduces Bayesian data analysis, allowing users to obtain uncertainty measurements easily for any derived parameter of interest Written in a step-by-step approach that allows for eased understanding by non-statisticians Includes a companion website containing R-code to help users conduct Bayesian data analyses on their own data All example data as well as additional functions are provided in the R-package blmeco
Book Synopsis Regression and Time Series Model Selection by : Allan D. R. McQuarrie
Download or read book Regression and Time Series Model Selection written by Allan D. R. McQuarrie and published by World Scientific. This book was released on 1998 with total page 479 pages. Available in PDF, EPUB and Kindle. Book excerpt: This important book describes procedures for selecting a model from a large set of competing statistical models. It includes model selection techniques for univariate and multivariate regression models, univariate and multivariate autoregressive models, nonparametric (including wavelets) and semiparametric regression models, and quasi-likelihood and robust regression models. Information-based model selection criteria are discussed, and small sample and asymptotic properties are presented. The book also provides examples and large scale simulation studies comparing the performances of information-based model selection criteria, bootstrapping, and cross-validation selection methods over a wide range of models.
Book Synopsis Information Criteria and Statistical Modeling by : Sadanori Konishi
Download or read book Information Criteria and Statistical Modeling written by Sadanori Konishi and published by Springer Science & Business Media. This book was released on 2008 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical modeling is a critical tool in scientific research. This book provides comprehensive explanations of the concepts and philosophy of statistical modeling, together with a wide range of practical and numerical examples. The authors expect this work to be of great value not just to statisticians but also to researchers and practitioners in various fields of research such as information science, computer science, engineering, bioinformatics, economics, marketing and environmental science. It’s a crucial area of study, as statistical models are used to understand phenomena with uncertainty and to determine the structure of complex systems. They’re also used to control such systems, as well as to make reliable predictions in various natural and social science fields.
Book Synopsis Modern Phylogenetic Comparative Methods and Their Application in Evolutionary Biology by : László Zsolt Garamszegi
Download or read book Modern Phylogenetic Comparative Methods and Their Application in Evolutionary Biology written by László Zsolt Garamszegi and published by Springer. This book was released on 2014-07-29 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: Phylogenetic comparative approaches are powerful analytical tools for making evolutionary inferences from interspecific data and phylogenies. The phylogenetic toolkit available to evolutionary biologists is currently growing at an incredible speed, but most methodological papers are published in the specialized statistical literature and many are incomprehensible for the user community. This textbook provides an overview of several newly developed phylogenetic comparative methods that allow to investigate a broad array of questions on how phenotypic characters evolve along the branches of phylogeny and how such mechanisms shape complex animal communities and interspecific interactions. The individual chapters were written by the leading experts in the field and using a language that is accessible for practicing evolutionary biologists. The authors carefully explain the philosophy behind different methodologies and provide pointers – mostly using a dynamically developing online interface – on how these methods can be implemented in practice. These “conceptual” and “practical” materials are essential for expanding the qualification of both students and scientists, but also offer a valuable resource for educators. Another value of the book are the accompanying online resources (available at: http://www.mpcm-evolution.com), where the authors post and permanently update practical materials to help embed methods into practice.
Book Synopsis Bayesian Analysis for Population Ecology by : Ruth King
Download or read book Bayesian Analysis for Population Ecology written by Ruth King and published by CRC Press. This book was released on 2009-10-30 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: Novel Statistical Tools for Conserving and Managing PopulationsBy gathering information on key demographic parameters, scientists can often predict how populations will develop in the future and relate these parameters to external influences, such as global warming. Because of their ability to easily incorporate random effects, fit state-space mode
Book Synopsis Bayesian Methods in Cosmology by : Michael P. Hobson
Download or read book Bayesian Methods in Cosmology written by Michael P. Hobson and published by Cambridge University Press. This book was released on 2010 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive introduction to Bayesian methods in cosmological studies, for graduate students and researchers in cosmology, astrophysics and applied statistics.
Book Synopsis Bayesian Forecasting and Dynamic Models by : Mike West
Download or read book Bayesian Forecasting and Dynamic Models written by Mike West and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book we are concerned with Bayesian learning and forecast ing in dynamic environments. We describe the structure and theory of classes of dynamic models, and their uses in Bayesian forecasting. The principles, models and methods of Bayesian forecasting have been developed extensively during the last twenty years. This devel opment has involved thorough investigation of mathematical and sta tistical aspects of forecasting models and related techniques. With this has come experience with application in a variety of areas in commercial and industrial, scientific and socio-economic fields. In deed much of the technical development has been driven by the needs of forecasting practitioners. As a result, there now exists a relatively complete statistical and mathematical framework, although much of this is either not properly documented or not easily accessible. Our primary goals in writing this book have been to present our view of this approach to modelling and forecasting, and to provide a rea sonably complete text for advanced university students and research workers. The text is primarily intended for advanced undergraduate and postgraduate students in statistics and mathematics. In line with this objective we present thorough discussion of mathematical and statistical features of Bayesian analyses of dynamic models, with illustrations, examples and exercises in each Chapter.
Book Synopsis The SAGE Handbook of Multilevel Modeling by : Marc A. Scott
Download or read book The SAGE Handbook of Multilevel Modeling written by Marc A. Scott and published by SAGE. This book was released on 2013-08-31 with total page 745 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this important new Handbook, the editors have gathered together a range of leading contributors to introduce the theory and practice of multilevel modeling. The Handbook establishes the connections in multilevel modeling, bringing together leading experts from around the world to provide a roadmap for applied researchers linking theory and practice, as well as a unique arsenal of state-of-the-art tools. It forges vital connections that cross traditional disciplinary divides and introduces best practice in the field. Part I establishes the framework for estimation and inference, including chapters dedicated to notation, model selection, fixed and random effects, and causal inference. Part II develops variations and extensions, such as nonlinear, semiparametric and latent class models. Part III includes discussion of missing data and robust methods, assessment of fit and software. Part IV consists of exemplary modeling and data analyses written by methodologists working in specific disciplines. Combining practical pieces with overviews of the field, this Handbook is essential reading for any student or researcher looking to apply multilevel techniques in their own research.
Book Synopsis Handbook of Advanced Multilevel Analysis by : Joop Hox
Download or read book Handbook of Advanced Multilevel Analysis written by Joop Hox and published by Routledge. This book was released on 2011-01-11 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new handbook is the definitive resource on advanced topics related to multilevel analysis. The editors assembled the top minds in the field to address the latest applications of multilevel modeling as well as the specific difficulties and methodological problems that are becoming more common as more complicated models are developed. Each chapter features examples that use actual datasets. These datasets, as well as the code to run the models, are available on the book’s website http://www.hlm-online.com . Each chapter includes an introduction that sets the stage for the material to come and a conclusion. Divided into five sections, the first provides a broad introduction to the field that serves as a framework for understanding the latter chapters. Part 2 focuses on multilevel latent variable modeling including item response theory and mixture modeling. Section 3 addresses models used for longitudinal data including growth curve and structural equation modeling. Special estimation problems are examined in section 4 including the difficulties involved in estimating survival analysis, Bayesian estimation, bootstrapping, multiple imputation, and complicated models, including generalized linear models, optimal design in multilevel models, and more. The book’s concluding section focuses on statistical design issues encountered when doing multilevel modeling including nested designs, analyzing cross-classified models, and dyadic data analysis. Intended for methodologists, statisticians, and researchers in a variety of fields including psychology, education, and the social and health sciences, this handbook also serves as an excellent text for graduate and PhD level courses in multilevel modeling. A basic knowledge of multilevel modeling is assumed.
Book Synopsis Cause and Correlation in Biology by : Bill Shipley
Download or read book Cause and Correlation in Biology written by Bill Shipley and published by Cambridge University Press. This book was released on 2002-08 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book goes beyond the truism that 'correlation does not imply causation' and explores the logical and methodological relationships between correlation and causation. It presents a series of statistical methods that can test, and potentially discover, cause-effect relationships between variables in situations in which it is not possible to conduct randomised or experimentally controlled experiments. Many of these methods are quite new and most are generally unknown to biologists. In addition to describing how to conduct these statistical tests, the book also puts the methods into historical context and explains when they can and cannot justifiably be used to test or discover causal claims. Written in a conversational style that minimises technical jargon, the book is aimed at practising biologists and advanced students, and assumes only a very basic knowledge of introductory statistics.
Book Synopsis Environmental Economics: A Simple Introduction by : K.H. Erickson
Download or read book Environmental Economics: A Simple Introduction written by K.H. Erickson and published by K.H. Erickson. This book was released on with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: Environmental Economics: A Simple Introduction offers an accessible guide to the central theories and methods of environmental economics, with examples, equations, and diagrams to support the analysis. Understand the problem of environmental degradation, and why environmental externalities and market failure cause pollution to spiral out of control. Examine the effectiveness of the polluters pay principle and a range of pollution control instruments, including bargaining, Pigovian taxation, tradable emissions permits, and command and control policy. Compare how each of the methods fare on cost efficiency, dynamic efficiency, equity, and performance under uncertainty. Explore efficient environmental management, and see how renewable natural resources can be harvested efficiently, and how a tragedy of the commons scenario can be avoided. Understand the conditions of the Hotelling rule for optimal extraction of non-renewable natural resources. Look at the stages of cost-benefit analysis and environmental policy valuation, and how the impacts of projects are valued using stated preference, revealed preference, or production function approaches.
