Regression Models, Methods and Applications, Ludwig Fahrmeir; Thomas Kneib; Stefan Lang; Brian
Новое издание
Автор: Fahrmeir Ludwig, Kneib Thomas, Lang Stefan Название: Regression: Models, Methods and Applications ISBN: 3662638819 ISBN-13(EAN): 9783662638811 Издательство: Springer Цена: 102480 T Описание: Now in its second edition, this textbook provides an applied and unified introduction to parametric, nonparametric and semiparametric regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal basis, and their appropriate application is shown through numerous examples and case studies. The most important definitions and statements are concisely summarized in boxes, and the underlying data sets and code are available online on the book’s dedicated website. Availability of (user-friendly) software has been a major criterion for the methods selected and presented. The chapters address the classical linear model and its extensions, generalized linear models, categorical regression models, mixed models, nonparametric regression, structured additive regression, quantile regression and distributional regression models. Two appendices describe the required matrix algebra, as well as elements of probability calculus and statistical inference. In this substantially revised and updated new edition the overview on regression models has been extended, and now includes the relation between regression models and machine learning, additional details on statistical inference in structured additive regression models have been added and a completely reworked chapter augments the presentation of quantile regression with a comprehensive introduction to distributional regression models. Regularization approaches are now more extensively discussed in most chapters of the book. The book primarily targets an audience that includes students, teachers and practitioners in social, economic, and life sciences, as well as students and teachers in statistics programs, and mathematicians and computer scientists with interests in statistical modeling and data analysis. It is written at an intermediate mathematical level and assumes only knowledge of basic probability, calculus, matrix algebra and statistics.
Автор: Gifford Robert Название: Research Methods for Environmental Psychology ISBN: 1118795385 ISBN-13(EAN): 9781118795385 Издательство: Wiley Рейтинг: Цена: 42190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Covering the full spectrum of methodology, the timely and indispensible Research Methods for Environmental surveys the research and application methods for studying, changing, and improving human attitudes, behaviour and well-being in relation to the physical environment.
Автор: Saenz, Benjamin Alire Название: Inexplicable logic of my life ISBN: 1471171035 ISBN-13(EAN): 9781471171031 Издательство: Simon&Schuster UK Рейтинг: Цена: 9890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A warmly humane look at universal questions of belonging, infused with humour, from the bestselling author of Aristotle and Dante Discover the Secrets of the Universe
Автор: Fahrmeir Ludwig, Kneib Thomas, Lang Stefan Название: Regression: Models, Methods and Applications ISBN: 3662638819 ISBN-13(EAN): 9783662638811 Издательство: Springer Рейтинг: Цена: 102480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Now in its second edition, this textbook provides an applied and unified introduction to parametric, nonparametric and semiparametric regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal basis, and their appropriate application is shown through numerous examples and case studies. The most important definitions and statements are concisely summarized in boxes, and the underlying data sets and code are available online on the book’s dedicated website. Availability of (user-friendly) software has been a major criterion for the methods selected and presented. The chapters address the classical linear model and its extensions, generalized linear models, categorical regression models, mixed models, nonparametric regression, structured additive regression, quantile regression and distributional regression models. Two appendices describe the required matrix algebra, as well as elements of probability calculus and statistical inference. In this substantially revised and updated new edition the overview on regression models has been extended, and now includes the relation between regression models and machine learning, additional details on statistical inference in structured additive regression models have been added and a completely reworked chapter augments the presentation of quantile regression with a comprehensive introduction to distributional regression models. Regularization approaches are now more extensively discussed in most chapters of the book. The book primarily targets an audience that includes students, teachers and practitioners in social, economic, and life sciences, as well as students and teachers in statistics programs, and mathematicians and computer scientists with interests in statistical modeling and data analysis. It is written at an intermediate mathematical level and assumes only knowledge of basic probability, calculus, matrix algebra and statistics.
Автор: Fox John Название: Applied Regression Analysis and Generalized Linear Models ISBN: 1452205663 ISBN-13(EAN): 9781452205663 Издательство: Sage Publications Рейтинг: Цена: 166850.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Providing a modern treatment of regression analysis, linear models and closely related methods, this book introduces students to one of the most useful and widely used statistical tools for social research.
Автор: Vittinghoff Название: Regression Methods in Biostatistics ISBN: 0387202757 ISBN-13(EAN): 9780387202754 Издательство: Springer Рейтинг: Цена: 75420.00 T Наличие на складе: Поставка под заказ. Описание: An introduction to the multipredictor regression methods widely used in biostatistics. This book covers linear models for continuous outcomes; logistic models for binary outcomes; the Cox model for right-censored survival times; repeated-measures models for longitudinal and hierarchical outcomes; and linear models for counts and other outcomes.
Автор: Hocking Ronald R Название: Methods and Applications of Linear Models ISBN: 1118329503 ISBN-13(EAN): 9781118329504 Издательство: Wiley Рейтинг: Цена: 134060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Praise for the Second Edition "An essential desktop reference book... it should definitely be on your bookshelf.
Автор: Hilbe Название: Logistic Regression Models ISBN: 1138106712 ISBN-13(EAN): 9781138106710 Издательство: Taylor&Francis Рейтинг: Цена: 58170.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Logistic Regression Models presents an overview of the full range of logistic models, including binary, proportional, ordered, partially ordered, and unordered categorical response regression procedures. Other topics discussed include panel, survey, skewed, penalized, and exact logistic models. The text illustrates how to apply the various models to health, environmental, physical, and social science data.
Examples illustrate successful modeling The text first provides basic terminology and concepts, before explaining the foremost methods of estimation (maximum likelihood and IRLS) appropriate for logistic models. It then presents an in-depth discussion of related terminology and examines logistic regression model development and interpretation of the results. After focusing on the construction and interpretation of various interactions, the author evaluates assumptions and goodness-of-fit tests that can be used for model assessment. He also covers binomial logistic regression, varieties of overdispersion, and a number of extensions to the basic binary and binomial logistic model. Both real and simulated data are used to explain and test the concepts involved. The appendices give an overview of marginal effects and discrete change as well as a 30-page tutorial on using Stata commands related to the examples used in the text. Stata is used for most examples while R is provided at the end of the chapters to replicate examples in the text.
Apply the models to your own data Data files for examples and questions used in the text as well as code for user-authored commands are provided on the book's website, formatted in Stata, R, Excel, SAS, SPSS, and Limdep.
See Professor Hilbe discuss the book.
Автор: Peter Martin Название: Regression Models for Categorical and Count Data ISBN: 1529762693 ISBN-13(EAN): 9781529762693 Издательство: Sage Publications Рейтинг: Цена: 25330.00 T Наличие на складе: Поставка под заказ. Описание:
This text provides practical guidance on conducting regression analysis on categorical and count data. Step by step and supported by lots of helpful graphs, it covers both the theoretical underpinnings of these methods as well as their application, giving you the skills needed to apply them to your own research. It offers guidance on:
· Using logistic regression models for binary, ordinal, and multinomial outcomes
· Applying count regression, including Poisson, negative binomial, and zero-inflated models
· Choosing the most appropriate model to use for your research
· The general principles of good statistical modelling in practice
Part of The SAGE Quantitative Research Kit, this book will give you the know-how and confidence needed to succeed on your quantitative research journey
Автор: Caroni Название: First Hitting Time Regression Models ISBN: 1848218893 ISBN-13(EAN): 9781848218895 Издательство: Wiley Рейтинг: Цена: 146730.00 T Наличие на складе: Поставка под заказ.
Автор: Eric Vittinghoff; David V. Glidden; Stephen C. Shi Название: Regression Methods in Biostatistics ISBN: 1489998543 ISBN-13(EAN): 9781489998545 Издательство: Springer Рейтинг: Цена: 79190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This fresh edition, substantially revised and augmented, provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics. The examples used, analyzed using Stata, can be applied to other areas.
Автор: Chi, Guangqing Zhu, Jun Название: Spatial regression models for the social sciences ISBN: 154430207X ISBN-13(EAN): 9781544302072 Издательство: Sage Publications Рейтинг: Цена: 88710.00 T Наличие на складе: Поставка под заказ. Описание: Focusing on the methods that are commonly used by social scientists, this text introduces the regression methods for analysing spatial data.
Автор: Dirk Speelman; Kris Heylen; Dirk Geeraerts Название: Mixed-Effects Regression Models in Linguistics ISBN: 3319888501 ISBN-13(EAN): 9783319888507 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
When data consist of grouped observations or clusters, and there is a risk that measurements within the same group are not independent, group-specific random effects can be added to a regression model in order to account for such within-group associations. Regression models that contain such group-specific random effects are called mixed-effects regression models, or simply mixed models. Mixed models are a versatile tool that can handle both balanced and unbalanced datasets and that can also be applied when several layers of grouping are present in the data; these layers can either be nested or crossed. In linguistics, as in many other fields, the use of mixed models has gained ground rapidly over the last decade. This methodological evolution enables us to build more sophisticated and arguably more realistic models, but, due to its technical complexity, also introduces new challenges. This volume brings together a number of promising new evolutions in the use of mixed models in linguistics, but also addresses a number of common complications, misunderstandings, and pitfalls. Topics that are covered include the use of huge datasets, dealing with non-linear relations, issues of cross-validation, and issues of model selection and complex random structures. The volume features examples from various subfields in linguistics. The book also provides R code for a wide range of analyses.
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