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Model Selection and Multimodel Inference

Author : Kenneth P. Burnham
Publisher : Springer Science & Business Media
Page : 512 pages
File Size : 24,8 MB
Release : 2007-05-28
Category : Mathematics
ISBN : 0387224564

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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.

Model Selection and Multimodel Inference

Author : Kenneth P. Burnham
Publisher : Springer Science & Business Media
Page : 512 pages
File Size : 27,66 MB
Release : 2003-12-04
Category : Mathematics
ISBN : 0387953647

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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.

The Spencers of Amberson Avenue

Author : Ethel Spencer
Publisher : University of Pittsburgh Press
Page : 208 pages
File Size : 47,78 MB
Release : 2010-09-24
Category : Biography & Autobiography
ISBN : 9780822971344

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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."

Model Selection and Inference

Author : Kenneth P. Burnham
Publisher : Springer Science & Business Media
Page : 373 pages
File Size : 39,50 MB
Release : 2013-11-11
Category : Mathematics
ISBN : 1475729170

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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.

Model Based Inference in the Life Sciences

Author : David R. Anderson
Publisher : Springer Science & Business Media
Page : 203 pages
File Size : 49,8 MB
Release : 2007-12-22
Category : Science
ISBN : 0387740759

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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.

Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan

Author : Franzi Korner-Nievergelt
Publisher : Academic Press
Page : 329 pages
File Size : 26,79 MB
Release : 2015-04-04
Category : Science
ISBN : 0128016787

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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

Information Criteria and Statistical Modeling

Author : Sadanori Konishi
Publisher : Springer Science & Business Media
Page : 282 pages
File Size : 20,62 MB
Release : 2008
Category : Business & Economics
ISBN : 0387718869

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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.

Regression and Time Series Model Selection

Author : Allan D. R. McQuarrie
Publisher : World Scientific
Page : 479 pages
File Size : 32,53 MB
Release : 1998
Category : Mathematics
ISBN : 9812385452

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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.

The SAGE Handbook of Multilevel Modeling

Author : Marc A. Scott
Publisher : SAGE
Page : 954 pages
File Size : 41,75 MB
Release : 2013-08-31
Category : Social Science
ISBN : 1473971314

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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.