Analyzing and Modeling Data and Knowledge, Martin Schader
Автор: Harald Baayen Название: Analyzing Linguistic Data ISBN: 0521709180 ISBN-13(EAN): 9780521709187 Издательство: Cambridge Academ Рейтинг: Цена: 6970.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A straightforward introduction to the statistical analysis of language, designed for those with a non-mathematical background. Using the leading statistics programme `R`, the reader is guided step-by-step through a range of data sets, aided by over 40 exercises with model answers. Suitable for all those working with quantitative language data.
Автор: Sokolowski Название: Modeling and Simulation for Analyzing Global Events ISBN: 0470478411 ISBN-13(EAN): 9780470478417 Издательство: Wiley Рейтинг: Цена: 16782.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: one-of-a-kind introduction to the theory and application of modeling and simulation techniques in the realm of international studies Modeling and Simulation for Analyzing Global Events provides an orientation to the theory and application of modeling and simulation techniques in social science disciplines.
Автор: Jamie D. Riggs Название: Handbook for Applied Modeling: Non-Gaussian and Correlated Data ISBN: 1316601056 ISBN-13(EAN): 9781316601051 Издательство: Cambridge Academ Рейтинг: Цена: 6019.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Designed for the applied practitioner, this book is a compact, entry-level guide to modeling and analyzing data that fail idealized assumptions. It explains and demonstrates core techniques, common pitfalls and data issues, and interpretation of model results, all with a focus on application, utility, and real-life data.
Автор: Brian Everitt; Sophia Rabe-Hesketh Название: Analyzing Medical Data Using S-PLUS ISBN: 1441931767 ISBN-13(EAN): 9781441931764 Издательство: Springer Рейтинг: Цена: 27251.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Each chapter consists of basic statistical theory, simple examples of S-PLUS code, plus more complex examples of S-PLUS code, and exercises.
Автор: Moltedo Ana Название: Analyzing Food Security Using Household Survey Data ISBN: 1464801339 ISBN-13(EAN): 9781464801334 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 4019.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: "Since the end of the Second World War, the international community has been focusing on reducing the number and the proportion of people who suffer from hunger. Over time it became clear that no single indicator would provide a comprehensive picture of the food security situation. Rather, a suite of indicators is necessary to describe food insecurity in all its dimensions. The demand for evidence-based policies, which brings together providers such as statistical offices and users of food security indicators including policy makers and researchers, has also been increasing. The stand-alone software, ADePT-Food Security Module (available for free downloading), was developed to produce food security indicators from food consumption data collected in household surveys. These indicators, derived at the national and subnational levels, include the consumption of calories and macronutrients, the availability of micronutrients and amino acids, the distribution of calories and the proportion of people undernourished. The book focuses on the theory, methodology, and analysis of these indicators. It has five chapters beginning with a brief overview on concepts of food security. The theory and methodology are further described in the following chapter. To help users with the interpretation of the results some examples are given in chapter 3. Chapter 4 of the book provides guidelines for the preparation of the input datasets. Finally, chapter 5 explains how to use the software. Both the software and this book are products of decades of experience in analyzing food security. This project was made possible through collaboration between FAO and the World Bank, with financial support from the European Union."
Автор: Jeffrey S. Simonoff Название: Analyzing Categorical Data ISBN: 144191837X ISBN-13(EAN): 9781441918376 Издательство: Springer Рейтинг: Цена: 12850.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Categorical data arise often in many fields, including biometrics, economics, management, manufacturing, marketing, psychology, and sociology. This book provides an introduction to the analysis of such data. The coverage is broad, using the loglinear Poisson regression model and logistic binomial regression models as the primary engines for methodology. Topics covered include count regression models, such as Poisson, negative binomial, zero-inflated, and zero-truncated models; loglinear models for two-dimensional and multidimensional contingency tables, including for square tables and tables with ordered categories; and regression models for two-category (binary) and multiple-category target variables, such as logistic and proportional odds models.
All methods are illustrated with analyses of real data examples, many from recent subject area journal articles. These analyses are highlighted in the text, and are more detailed than is typical, providing discussion of the context and background of the problem, model checking, and scientific implications. More than 200 exercises are provided, many also based on recent subject area literature. Data sets and computer code are available at a web site devoted to the text. Adopters of this book may request a solutions manual from: textbook@springer-ny.com.
From the reviews:
"Jeff Simonoff's book is at the top of the heap of categorical data analysis textbooks...The examples are superb. Student reactions in a class I taught from this text were uniformly positive, particularly because of the examples and exercises. Additional materials related to the book, particularly code for S-Plus, SAS, and R, useful for analysis of examples, can be found at the author's Web site at New York University. I liked this book for this reason, and recommend it to you for pedagogical purposes." (Stanley Wasserman, The American Statistician, August 2006, Vol. 60, No. 3)
"The book has various noteworthy features. The examples used are from a variety of topics, including medicine, economics, sports, mining, weather, as well as social aspects like needle-exchange programs. The examples motivate the theory and also illustrate nuances of data analytical procedures. The book also incorporates several newer methods for analyzing categorical data, including zero-inflated Poisson models, robust analysis of binomial and poisson models, sandwich estimators, multinomial smoothing, ordinal agreement tables...this is definitely a good reference book for any researcher working with categorical data." Technometrics, May 2004
"This guide provides a practical approach to the appropriate analysis of categorical data and would be a suitable purchase for individuals with varying levels of statistical understanding." Paediatric and Perinatal Epidemiology, 2004, 18
"This book gives a fresh approach to the topic of categorical data analysis. The presentation of the statistical methods exploits the connection to regression modeling with a focus on practical features rather than formal theory...There is much to learn from this book. Aside from the ordinary materials such as association diagrams, Mantel-Haenszel estimators, or overdispersion, the reader will also find some less-often presented but interesting and stimulating topics... T]his is an excellent book, giving an up-to-date introduction to the wide field of analyzing categorical data." Biometrics, September 2004
..".It is of great help to data
Автор: Douglas E. Critchlow Название: Metric Methods for Analyzing Partially Ranked Data ISBN: 0387962883 ISBN-13(EAN): 9780387962887 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A full ranking of n items is simply an ordering of all these items, of the form: first choice, second choice, *. The problem thus becomes one of ex- tending metrics on the permutation group to metrics on a coset space of the permutation group.
Автор: Wolfgang A. Gaul; Martin Schader Название: Data, Expert Knowledge and Decisions ISBN: 364273491X ISBN-13(EAN): 9783642734915 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Concrete interconnections between data analysis and marketing can be seen in the contributions on classification and unfolding of market data, market segmentation by forced classification, conjoint analysis applications, ideal point product mapping, MDS in telecommunications pricing and multi-mode marketing data evaluations.
Автор: van den Boogaart, K. Gerald, Tolosana-Delgado, Raimon Название: Analyzing Compositional Data with R ISBN: 3642368085 ISBN-13(EAN): 9783642368080 Издательство: Springer Рейтинг: Цена: 7406.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book covers statistical analysis of compositional data sets from basic principles to applications in descriptive exploratory analysis, robust linear models and advanced multivariate statistical methods. Offers many illustrated examples and code chunks.
Автор: Hans-Hermann Bock; Peter Ihm Название: Classification, Data Analysis, and Knowledge Organization ISBN: 3540534830 ISBN-13(EAN): 9783540534839 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Proceedings of the 14th Annual Conference of the Gesellschaft fur Klassifikation e.V., University of Marburg March 12-14, 1990
Автор: O. Maimon; M. Last Название: Knowledge Discovery and Data Mining ISBN: 1441948422 ISBN-13(EAN): 9781441948427 Издательство: Springer Рейтинг: Цена: 19559.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents a specific and unified approach to Knowledge Discovery and Data Mining, termed IFN for Information Fuzzy Network methodology. Data Mining (DM) is the science of modelling and generalizing common patterns from large sets of multi-type data. DM is a part of KDD, which is the overall process for Knowledge Discovery in Databases. The accessibility and abundance of information today makes this a topic of particular importance and need. The book has three main parts complemented by appendices as well as software and project data that are accessible from the book's web site (http: //www.eng.tau.ac.iV-maimonlifn-kdg ). Part I (Chapters 1-4) starts with the topic of KDD and DM in general and makes reference to other works in the field, especially those related to the information theoretic approach. The remainder of the book presents our work, starting with the IFN theory and algorithms. Part II (Chapters 5-6) discusses the methodology of application and includes case studies. Then in Part III (Chapters 7-9) a comparative study is presented, concluding with some advanced methods and open problems. The IFN, being a generic methodology, applies to a variety of fields, such as manufacturing, finance, health care, medicine, insurance, and human resources. The appendices expand on the relevant theoretical background and present descriptions of sample projects (including detailed results).
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