Автор: Gelfand, Alan E. Fuentes, Montserrat Guttorp, Pete Название: Handbook of spatial statistics ISBN: 1420072870 ISBN-13(EAN): 9781420072877 Издательство: Taylor&Francis Рейтинг: Цена: 103610.00 T Наличие на складе: Есть Описание: Offers an introduction detailing the evolution of the field of spatial statistics. This title focuses on the three main branches of spatial statistics: continuous spatial variation (point referenced data); discrete spatial variation, including lattice and areal unit data; and, spatial point patterns.
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: Chatterjee Samprit, Simonoff Jeffrey S. Название: Handbook of Regression Analysis with Applications in R ISBN: 1119392373 ISBN-13(EAN): 9781119392378 Издательство: Wiley Рейтинг: Цена: 117160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Handbook and reference guide for students and practitioners of statistical regression-based analyses in R
Handbook of Regression Analysis with Applications in R, Second Edition is a comprehensive and up-to-date guide to conducting complex regressions in the R statistical programming language. The authors' thorough treatment of "classical" regression analysis in the first edition is complemented here by their discussion of more advanced topics including time-to-event survival data and longitudinal and clustered data.
The book further pays particular attention to methods that have become prominent in the last few decades as increasingly large data sets have made new techniques and applications possible. These include:
In the new edition of the Handbook, the data analyst's toolkit is explored and expanded. Examples are drawn from a wide variety of real-life applications and data sets. All the utilized R code and data are available via an author-maintained website.
Of interest to undergraduate and graduate students taking courses in statistics and regression, the Handbook of Regression Analysis will also be invaluable to practicing data scientists and statisticians.
Автор: Chatterjee Samprit Название: Handbook of Regression Analysis ISBN: 0470887168 ISBN-13(EAN): 9780470887165 Издательство: Wiley Рейтинг: Цена: 125610.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A Comprehensive Account for Data Analysts of the Methods and Applications of Regression Analysis. Written by two established experts in the field, the purpose of the Handbook of Regression Analysis is to provide a practical, one-stop reference on regression analysis.
Автор: Mcnulty, Keith Название: Handbook of regression modeling in people analytics ISBN: 1032041749 ISBN-13(EAN): 9781032041742 Издательство: Taylor&Francis Рейтинг: Цена: 68390.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book is a learning resource on inferential statistics and regression analysis. It teaches how to do a wide range of statistical analyses in both R and in Python, ranging from simple hypothesis testing to advanced multivariate modelling.
Название: Sage handbook of regression analysis and causal inference ISBN: 1446252442 ISBN-13(EAN): 9781446252444 Издательство: Sage Publications Рейтинг: Цена: 142560.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Название: Handbook of Quantile Regression ISBN: 1498725287 ISBN-13(EAN): 9781498725286 Издательство: Taylor&Francis Рейтинг: Цена: 163330.00 T Наличие на складе: Нет в наличии.
Автор: Koenker, Roger Название: Handbook of Quantile Regression ISBN: 0367657570 ISBN-13(EAN): 9780367657574 Издательство: Taylor&Francis Рейтинг: Цена: 51030.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Grace Y. Yi, Aurore Delaigle, Paul Gustafson Название: Handbook of Measurement Error Models ISBN: 1138106402 ISBN-13(EAN): 9781138106406 Издательство: Taylor&Francis Рейтинг: Цена: 219470.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Reference text for statistical methods and applications for measurement error models for: researchers who work with error-contaminated data, graduate students from statistics and biostatistics, analysts in multiple fields, including medical research, biosciences, nutritional studies, epidemiological studies and environmental studies.
Автор: Paulson, Daryl S. Название: Handbook of Regression and Modeling ISBN: 1032477857 ISBN-13(EAN): 9781032477855 Издательство: Taylor&Francis Рейтинг: Цена: 46950.00 T Наличие на складе: Нет в наличии.
Автор: Paulson, Daryl S. Название: Handbook of Regression and Modeling ISBN: 157444610X ISBN-13(EAN): 9781574446104 Издательство: Taylor&Francis Рейтинг: Цена: 163330.00 T Наличие на складе: Нет в наличии.
Автор: von Rosen Название: Bilinear Regression Analysis ISBN: 3319787829 ISBN-13(EAN): 9783319787824 Издательство: Springer Рейтинг: Цена: 69870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book expands on the classical statistical multivariate analysis theory by focusing on bilinear regression models, a class of models comprising the classical growth curve model and its extensions. In order to analyze the bilinear regression models in an interpretable way, concepts from linear models are extended and applied to tensor spaces. Further, the book considers decompositions of tensor products into natural subspaces, and addresses maximum likelihood estimation, residual analysis, influential observation analysis and testing hypotheses, where properties of estimators such as moments, asymptotic distributions or approximations of distributions are also studied. Throughout the text, examples and several analyzed data sets illustrate the different approaches, and fresh insights into classical multivariate analysis are provided. This monograph is of interest to researchers and Ph.D. students in mathematical statistics, signal processing and other fields where statistical multivariate analysis is utilized. It can also be used as a text for second graduate-level courses on multivariate analysis.
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