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Regression Models, Methods and Applications, Ludwig Fahrmeir; Thomas Kneib; Stefan Lang; Brian


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Автор: Ludwig Fahrmeir; Thomas Kneib; Stefan Lang; Brian
Название:  Regression Models, Methods and Applications
ISBN: 9783662638828
Издательство: Springer
Классификация: ISBN-10: 3662638827
Вес: 0.00 кг.
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Поставляется из: Германии


      Новое издание
Regression: Models, Methods and Applications

Автор: Fahrmeir Ludwig, Kneib Thomas, Lang Stefan
Название: Regression: Models, Methods and Applications
ISBN: 3662638819 ISBN-13(EAN): 9783662638811
Издательство: Springer
Цена: 15372.00 р.
Наличие на складе: Есть у поставщикаПоставка 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.


Research Methods for Environmental Psychology

Автор: Gifford Robert
Название: Research Methods for Environmental Psychology
ISBN: 1118795385 ISBN-13(EAN): 9781118795385
Издательство: Wiley
Рейтинг:
Цена: 6328.00 р.
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.

Inexplicable logic of my life

Автор: Saenz, Benjamin Alire
Название: Inexplicable logic of my life
ISBN: 1471171035 ISBN-13(EAN): 9781471171031
Издательство: Simon&Schuster UK
Рейтинг:
Цена: 1483.00 р.
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

Regression: Models, Methods and Applications

Автор: Fahrmeir Ludwig, Kneib Thomas, Lang Stefan
Название: Regression: Models, Methods and Applications
ISBN: 3662638819 ISBN-13(EAN): 9783662638811
Издательство: Springer
Рейтинг:
Цена: 15372.00 р.
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.

Applied Regression Analysis and Generalized Linear Models

Автор: Fox John
Название: Applied Regression Analysis and Generalized Linear Models
ISBN: 1452205663 ISBN-13(EAN): 9781452205663
Издательство: Sage Publications
Рейтинг:
Цена: 25027.00 р.
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.

Mixed-Effects Regression Models in Linguistics

Автор: Dirk Speelman; Kris Heylen; Dirk Geeraerts
Название: Mixed-Effects Regression Models in Linguistics
ISBN: 3319698281 ISBN-13(EAN): 9783319698281
Издательство: Springer
Рейтинг:
Цена: 13974.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: When data consists of grouped observations or clusters, and there is a risk that measurements within the same groups are not independent, group-specific random effects can be added to a regression model in order to account for such within-group associations.

First Hitting Time Regression Models

Автор: Caroni
Название: First Hitting Time Regression Models
ISBN: 1848218893 ISBN-13(EAN): 9781848218895
Издательство: Wiley
Рейтинг:
Цена: 22010.00 р.
Наличие на складе: Поставка под заказ.

Regression Models for the Comparison of Measurement Methods

Автор: Bolfarine Heleno, de Castro Mбrio, Galea Manuel
Название: Regression Models for the Comparison of Measurement Methods
ISBN: 3030579344 ISBN-13(EAN): 9783030579340
Издательство: Springer
Цена: 6986.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book provides an updated account of the regression techniques employed in comparing analytical methods and to test the biases of one method relative to others - a problem commonly found in fields like analytical chemistry, biology, engineering, and medicine.

Regression

Автор: Fahrmeir Ludwig
Название: Regression
ISBN: 3642343325 ISBN-13(EAN): 9783642343322
Издательство: Springer
Рейтинг:
Цена: 13974.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Thus, 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.

Methods and Applications of Linear Models

Автор: Hocking Ronald R
Название: Methods and Applications of Linear Models
ISBN: 1118329503 ISBN-13(EAN): 9781118329504
Издательство: Wiley
Рейтинг:
Цена: 20109.00 р.
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.

Logistic Regression Models

Автор: Hilbe
Название: Logistic Regression Models
ISBN: 1138106712 ISBN-13(EAN): 9781138106710
Издательство: Taylor&Francis
Рейтинг:
Цена: 8726.00 р.
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.

Regression Models for Categorical and Count Data

Автор: Peter Martin
Название: Regression Models for Categorical and Count Data
ISBN: 1529762693 ISBN-13(EAN): 9781529762693
Издательство: Sage Publications
Рейтинг:
Цена: 3800.00 р.
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

Regression Methods in Biostatistics

Автор: Eric Vittinghoff; David V. Glidden; Stephen C. Shi
Название: Regression Methods in Biostatistics
ISBN: 1489998543 ISBN-13(EAN): 9781489998545
Издательство: Springer
Рейтинг:
Цена: 11878.00 р.
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.


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