Analysis of Incomplete Multivariate Data, Schafer, J.L.
Автор: Janos Fodor; Bernard De Baets; Patrice Perny Название: Preferences and Decisions under Incomplete Knowledge ISBN: 3790813036 ISBN-13(EAN): 9783790813036 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Decision problems are pervaded with incomplete knowledge - imprecision and/or uncertain information, both in the problem description and in the preferential information. This volume addresses various theoretical and practical aspects related to the handling of this incompleteness.
Описание: Investigates optimal investment problems for stochastic financial market models. This work is intended for academics and students who are interested in the mathematics of finance, stochastic processes, and optimal control, and also for practitioners in risk management and quantitative analysis.
Автор: Hougaard Philip Название: Analysis of Multivariate Survival Data ISBN: 1461270871 ISBN-13(EAN): 9781461270874 Издательство: Springer Рейтинг: Цена: 7406.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Survival data or more general time-to-event data occur in many areas, including medicine, biology, engineering, economics, and demography, but previously standard methods have requested that all time variables are univariate and independent. As the field is rather new, the concepts and the possible types of data are described in detail.
Автор: Ewa Orlowska Название: Incomplete Information: Rough Set Analysis ISBN: 3790810495 ISBN-13(EAN): 9783790810493 Издательство: Springer Рейтинг: Цена: 27251.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is an account of the current status of the basic theory, extensions and applications of rough sets. The book presents rough set formalisms and methods of modelling and handling incomplete information, and motivates their applicability to knowledge discovery and machine learning.
Автор: Wu Название: Robust Latent Feature Learning for Incomplete Big Data ISBN: 9811981396 ISBN-13(EAN): 9789811981395 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Incomplete big data are frequently encountered in many industrial applications, such as recommender systems, the Internet of Things, intelligent transportation, cloud computing, and so on. It is of great significance to analyze them for mining rich and valuable knowledge and patterns. Latent feature analysis (LFA) is one of the most popular representation learning methods tailored for incomplete big data due to its high accuracy, computational efficiency, and ease of scalability. The crux of analyzing incomplete big data lies in addressing the uncertainty problem caused by their incomplete characteristics. However, existing LFA methods do not fully consider such uncertainty. In this book, the author introduces several robust latent feature learning methods to address such uncertainty for effectively and efficiently analyzing incomplete big data, including robust latent feature learning based on smooth L1-norm, improving robustness of latent feature learning using L1-norm, improving robustness of latent feature learning using double-space, data-characteristic-aware latent feature learning, posterior-neighborhood-regularized latent feature learning, and generalized deep latent feature learning. Readers can obtain an overview of the challenges of analyzing incomplete big data and how to employ latent feature learning to build a robust model to analyze incomplete big data. In addition, this book provides several algorithms and real application cases, which can help students, researchers, and professionals easily build their models to analyze incomplete big data.
Автор: Kim Jae Kwang, Shao Jun Название: Statistical Methods for Handling Incomplete Data ISBN: 036728054X ISBN-13(EAN): 9780367280543 Издательство: Taylor&Francis Рейтинг: Цена: 17609.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Due to recent theoretical findings and advances in statistical computing, there has been a rapid development of techniques and applications in the area of missing data analysis. This book covers the most up-to-date statistical theories and computational methods for analyzing incomplete data.
Автор: Chaudhry, M. Aslam Название: On a Class of Incomplete Gamma Functions with Applications ISBN: 1584881437 ISBN-13(EAN): 9781584881438 Издательство: Taylor&Francis Рейтинг: Цена: 29093.00 р. Наличие на складе: Поставка под заказ.
Описание: We can distinguish between games which focus on strategic elements like games with incomplete information (see, for example, P`ng (1983), Samuelson (1982) and Schweizer (1989" and decision-theoretic models neglecting strategic elements (see, for example, Landes (1971) and Gould (1973".
Автор: Bo Shen; Zidong Wang; Huisheng Shu Название: Nonlinear Stochastic Systems with Incomplete Information ISBN: 1447160002 ISBN-13(EAN): 9781447160007 Издательство: Springer Рейтинг: Цена: 16977.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Nonlinear Stochastic Processes shows the reader how to deal with the issue of network-induced incomplete information. It presents a unified framework for filtering and control problems in complex communication networks with limited bandwidth.
Автор: Zadora Grzegorz Название: Statistical Analysis in Forensic Science ISBN: 0470972106 ISBN-13(EAN): 9780470972106 Издательство: Wiley Рейтинг: Цена: 12189.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides the methods and software to enable statisticians and forensic experts to work effectively with evidence evaluation methods. It also covers a collection of recent likelihood ratio (LR) approaches, explores suitable software toolboxes, and includes documentation and examples about how to use them in practice.
Автор: J.D. Jobson Название: Applied Multivariate Data Analysis ISBN: 1461269601 ISBN-13(EAN): 9781461269601 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An easy to read survey of data analysis, linear regression models and analysis of variance. The extensive development of the linear model includes the use of the linear model approach to analysis of variance provides a strong link to statistical software packages, and is complemented by a thorough overview of theory.
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