Statistical Methods for Spatial Data Analysis, Schabenberger, Oliver
Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman Название: The Elements of Statistical Learning ISBN: 0387848576 ISBN-13(EAN): 9780387848570 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.
Название: Analysis of Distributional Data ISBN: 1498725457 ISBN-13(EAN): 9781498725453 Издательство: Taylor&Francis Рейтинг: Цена: 17609.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In the era of "Big Data," distributional data is becoming more prevalent. This book presents a synthesis of research in this area over the last twenty years. It has been carefully edited to ensure it is consistent with respect to style, level, notation. Each chapter includes examples to illustrate the topics and software where appropriate.
Автор: Schabenberger, Oliver Название: Statistical Methods for Spatial Data Analysis ISBN: 1032477911 ISBN-13(EAN): 9781032477916 Издательство: Taylor&Francis Рейтинг: Цена: 7195.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: * Presents a much-needed practical guide to statistical spatial analysis on a network, in a logical, user-friendly order. * Introduces the preliminary methods involved, before detailing the advanced, computational methods, enabling the readers a complete understanding of the advanced topics.
Автор: Christopher H Schmid Название: Handbook Of Meta-Analysis ISBN: 1498703984 ISBN-13(EAN): 9781498703987 Издательство: Taylor&Francis Рейтинг: Цена: 24499.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Meta-analysis is the application of statistics to combine results from multiple studies and draw appropriate inferences. Its use and importance have exploded over the years as the need for a robust evidence base has become clear in many scientific areas like medicine and health, social sciences, education, psychology, ecology and economics.
Автор: He, Yulei Название: Multiple Imputation Analysis For Ob ISBN: 1498722067 ISBN-13(EAN): 9781498722063 Издательство: Taylor&Francis Рейтинг: Цена: 13779.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Multiple Imputation of Missing Data in Practice: Basic Theory and Analysis Strategies provides a comprehensive introduction to the multiple imputation approach to missing data problems that are often encountered in data analysis.
Автор: Eric D. Kolaczyk Название: Statistical Analysis of Network Data ISBN: 144192776X ISBN-13(EAN): 9781441927767 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In recent years there has been an explosion of network data - that is, measu- ments that are either of or from a system conceptualized as a network - from se- ingly all corners of science.
Автор: Brandt Siegmund Название: Data Analysis ISBN: 3319037617 ISBN-13(EAN): 9783319037615 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents a comprehensive introduction to statistical and numerical methods for the evaluation of empirical and experimental data. It includes example programs and solutions to programming problems written in Java.
Автор: Lewis Название: Complex Survey Data Analysis with SAS ISBN: 1498776779 ISBN-13(EAN): 9781498776776 Издательство: Taylor&Francis Рейтинг: Цена: 13779.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Complex Survey Data Analysis with SAS (R) is an invaluable resource for applied researchers analyzing data generated from a sample design involving any combination of stratification, clustering, unequal weights, or finite population correction factors.
Автор: Wang Название: Analysis of Longitudinal Data by Example ISBN: 1498764606 ISBN-13(EAN): 9781498764605 Издательство: Taylor&Francis Рейтинг: Цена: 13779.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Currently, there are a lack of intermediate /advanced level textbooks which introduce students and practicing statisticians to the updated methods on correlated data inference. T
Автор: Milliken Название: Analysis of Messy Data, Volume III ISBN: 158488083X ISBN-13(EAN): 9781584880837 Издательство: Taylor&Francis Рейтинг: Цена: 24499.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Analysis of covariance is a very useful but often misunderstood methodology for analyzing data where important characteristics of the experimental units are measured but not included as factors in the design. With a balance of theory and examples, this volume provides a guide to this strategy`s techniques, theory, and application.
Автор: Christensen Название: Analysis Of Variance, Design & Regr ISBN: 1498730140 ISBN-13(EAN): 9781498730143 Издательство: Taylor&Francis Рейтинг: Цена: 17609.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data, Second Edition presents linear structures for modeling data with an emphasis on how to incorporate specific ideas (hypotheses) about the structure of the data into a linear model for the data. The book carefully analyzes small data sets by using tools that are easily scaled to big data. The tools also apply to small relevant data sets that are extracted from big data.
New to the Second Edition
Reorganized to focus on unbalanced data
Reworked balanced analyses using methods for unbalanced data
Introductions to nonparametric and lasso regression
Introductions to general additive and generalized additive models
Examination of homologous factors
Unbalanced split plot analyses
Extensions to generalized linear models
R, Minitab(R), and SAS code on the author's website
The text can be used in a variety of courses, including a yearlong graduate course on regression and ANOVA or a data analysis course for upper-division statistics students and graduate students from other fields. It places a strong emphasis on interpreting the range of computer output encountered when dealing with unbalanced data.
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