Exploratory Data Analysis in Empirical Research / Proceedings of the 25th Annual Conference of the Gesellschaft fÃ¼r Klassifikation e.V., University of Munich, March 14-16, 2001, Schwaiger Manfred, Opitz Otto

Àâòîð: Philip Hans Franses Íàçâàíèå: Quantitative Models in Marketing Research ISBN: 0521801664 ISBN-13(EAN): 9780521801669 Èçäàòåëüñòâî: Cambridge Academ Ðåéòèíã: Öåíà: 8183 ð. Íàëè÷èå íà ñêëàäå: Ïîñòàâêà ïîä çàêàç.

Îïèñàíèå: Recent advances in data collection and data storage techniques enable marketing researchers to study the individual characteristics of a large range of transactions and purchases, in particular the effects of household-specific characteristics. This book presents the most important and practically relevant quantitative models for marketing research. Each model is presented in detail with a self-contained discussion, which includes: a demonstration of the mechanics of the model, empirical analysis, real world examples, and interpretation of results and findings. The reader of the book will learn how to apply the techniques, as well as understand the latest methodological developments in the academic literature. Pathways are offered in the book for students and practitioners with differing numerical skill levels; a basic knowledge of elementary numerical techniques is assumed.

Îïèñàíèå: An overview of data mining technology and how it is applied in a business environment. Methodologies are described that solve a variety of business problems and enhance firm-level efficiency in a less technical, managerial style. The book also incorporates the data mining process into the spectrum of complementary technologies that together comprise corporate information systems that promote "business intelligence". Business intelligence involves the proliferation of value-added information throughout a given enterprise through the use of various software applications that promote efficiency for the firm.

Àâòîð: Philip Hans Franses Íàçâàíèå: Non-linear time series models in empirical finance ISBN: 0521779650 ISBN-13(EAN): 9780521779654 Èçäàòåëüñòâî: Cambridge Academ Ðåéòèíã: Öåíà: 6071 ð. Íàëè÷èå íà ñêëàäå: Ïîñòàâêà ïîä çàêàç.

Îïèñàíèå: Although many of the models commonly used in empirical finance are linear, the nature of financial data suggests that non-linear models are more appropriate for forecasting and accurately describing returns and volatility. The enormous number of non-linear time series models appropriate for modeling and forecasting economic time series models makes choosing the best model for a particular application daunting. This classroom-tested advanced undergraduate and graduate textbook - the most up to-date and accessible guide available - provides a rigorous treatment of recently developed non-linear models, including regime-switching and artificial neural networks. The focus is on the potential applicability for describing and forecasting financial asset returns and their associated volatility. The models are analysed in detail and are not treated as ‘black boxes’. Illustrated using a wide range of financial data, drawn from sources including the financial markets of Tokyo, London and Frankfurt.

Îïèñàíèå: This practical resource presents modern, statistical methods for accelerated testing including test models, analyses of data, and plans for testing. Each topic is self-contained for easy reference. Coverage is broad and detailed enough to serve as a text or reference. This handy book features real test examples along with data analyses, computer programs, and references to the literature.

Àâòîð: Tsiatis Íàçâàíèå: Semiparametric Theory and Missing Data ISBN: 0387324488 ISBN-13(EAN): 9780387324487 Èçäàòåëüñòâî: Springer Ðåéòèíã: Öåíà: 17967 ð. Íàëè÷èå íà ñêëàäå: Ïîñòàâêà ïîä çàêàç.

Îïèñàíèå: This book summarizes current knowledge of the theory of estimation for semiparametric models with missing data, applying modern methods to missing, censored, and coarsened data with the goal of deriving estimators that are as robust and efficient as possible.

Îïèñàíèå: A presentation of statistical methods that features the use of graphical displays for exploring data and for displaying the analysis. This work demonstrates how to analyze data - showing code, graphics, and accompanying computer listings - for all the methods they cover. It emphasizes on how to construct and interpret graphs.

Îïèñàíèå: This book is intended for both undergraduate and graduate students in all branches of Earth science needing an introduction to any aspect of data treatment in connection with thesis preparation or writing up a project. It will also aid professional earth scientists to make the most of the interpretation of numerical data using spreadsheets and non-specialized commercial software. This is not merely a traditional statistics primer, it covers sampling, time series, orientation data in two and three dimensions and is very well illustrated with meaningful examples.

Àâòîð: Rudolf J. Freund Íàçâàíèå: Regression Analysis Study Guide, ISBN: 0123725046 ISBN-13(EAN): 9780123725042 Èçäàòåëüñòâî: Elsevier Science Ðåéòèíã: Öåíà: 3638 ð. Íàëè÷èå íà ñêëàäå: Åñòü ó ïîñòàâùèêà Ïîñòàâêà ïîä çàêàç.

Îïèñàíèå: This Special Issue presents proceedings of the International Conference on Behavioral Health and Traumatic Brain Injury convened in October 2008 that brought together over 100 international scientists, health care professionals, policy makers, US Military personnel, and family members, addressing the issues of mild traumatic brain injury and post traumatic stress disorder in the military.

Îïèñàíèå: Scientists today collect samples of curves and other functional observations. This monograph presents many ideas and techniques for such data. Included are expressions in the functional domain of such classics as linear regression, principal components analysis, linear modelling, and canonical correlation analysis, as well as specifically functional techniques such as curve registration and principal differential analysis. Data arising in real applications are used throughout for both motivation and illustration, showing how functional approaches allow us to see new things, especially by exploiting the smoothness of the processes generating the data. The data sets exemplify the wide scope of functional data analysis; they are drwan from growth analysis, meterology, biomechanics, equine science, economics, and medicine.The book presents novel statistical technology while keeping the mathematical level widely accessible. It is designed to appeal to students, to applied data analysts, and to experienced researchers; it will have value both within statistics and across a broad spectrum of other fields. Much of the material is based on the authors' own work, some of which appears here for the first time.Jim Ramsay is Professor of Psychology at McGill University and is an international authority on many aspects of multivariate analysis. He draws on his collaboration with researchers in speech articulation, motor control, meteorology, psychology, and human physiology to illustrate his technical contributions to functional data analysis in a wide range of statistical and application journals.Bernard Silverman, author of the highly regarded "Density Estimation for Statistics and Data Analysis," and coauthor of "Nonparametric Regression and Generalized Linear Models: A Roughness Penalty Approach," is Professor of Statistics at Bristol University. His published work on smoothing methods and other aspects of applied, computational, and theoretical statistics has been recognized by the Presidents' Award of the Committee of Presidents of Statistical Societies, and the award of two Guy Medals by the Royal Statistical Society.

Îïèñàíèå: This text provides an introduction to modern techniques in survival analysis at a level suitable for most researchers. Counting methods have been presented in other books but only at a much higher mathematical level.

Àâòîð: Ian Cobb Íàçâàíèå: Data Warehousing and the Management Accountant, ISBN: 1859714900 ISBN-13(EAN): 9781859714904 Èçäàòåëüñòâî: Elsevier Science Ðåéòèíã: Öåíà: 4890 ð. Íàëè÷èå íà ñêëàäå: Ïîñòàâêà ïîä çàêàç.

Îïèñàíèå: Details the findings from a questionnaire survey and a field study of data warehousing and its implications for management accountants and management accounting. This report suggests that management accountants are actively involved in shaping the direction of data warehousing in their organizations.