Evaluation of Statistical Matching and Selected SAE Methods, Verena Puchner
Автор: Prem K. Goel; Thirugnanasambandam Ramalingam Название: The Matching Methodology: Some Statistical Properties ISBN: 0387969705 ISBN-13(EAN): 9780387969701 Издательство: Springer Рейтинг: Цена: 107130.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Incomplete-data problems arise naturally in many instances of statistical practice. One main problem still to be resolved is the development of appropriate inference methodology from merged files if one insists on using file merging methodology.
Автор: Guy Gogniat; Dragomir Milojevic; Adam Morawiec; Ah Название: Algorithm-Architecture Matching for Signal and Image Processing ISBN: 9400733925 ISBN-13(EAN): 9789400733923 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Coverage of Algorithm-Architecture Matching ranges from sensors to architectures design, reflecting a diversity of potential algorithms including signal, communication, image, video, 3D-Graphics implemented onto architectures from FPGA to multiprocessor systems.
Автор: Agarwal Название: Statistical Methods for Recommender Systems ISBN: 1107036070 ISBN-13(EAN): 9781107036079 Издательство: Cambridge Academ Рейтинг: Цена: 50680.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Designing algorithms to recommend items such as news articles and movies to users is a challenging task in numerous web applications. The crux of the problem is to rank items based on users' responses to different items to optimize for multiple objectives. Major technical challenges are high dimensional prediction with sparse data and constructing high dimensional sequential designs to collect data for user modeling and system design. This comprehensive treatment of the statistical issues that arise in recommender systems includes detailed, in-depth discussions of current state-of-the-art methods such as adaptive sequential designs (multi-armed bandit methods), bilinear random-effects models (matrix factorization) and scalable model fitting using modern computing paradigms like MapReduce. The authors draw upon their vast experience working with such large-scale systems at Yahoo! and LinkedIn, and bridge the gap between theory and practice by illustrating complex concepts with examples from applications they are directly involved with.
Автор: Hastie Название: Statistical Learning with Sparsity ISBN: 1498712169 ISBN-13(EAN): 9781498712163 Издательство: Taylor&Francis Рейтинг: Цена: 112290.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Discover New Methods for Dealing with High-Dimensional Data
A sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underlying signal in a set of data.
Top experts in this rapidly evolving field, the authors describe the lasso for linear regression and a simple coordinate descent algorithm for its computation. They discuss the application of ℓ1 penalties to generalized linear models and support vector machines, cover generalized penalties such as the elastic net and group lasso, and review numerical methods for optimization. They also present statistical inference methods for fitted (lasso) models, including the bootstrap, Bayesian methods, and recently developed approaches. In addition, the book examines matrix decomposition, sparse multivariate analysis, graphical models, and compressed sensing. It concludes with a survey of theoretical results for the lasso.
In this age of big data, the number of features measured on a person or object can be large and might be larger than the number of observations. This book shows how the sparsity assumption allows us to tackle these problems and extract useful and reproducible patterns from big datasets. Data analysts, computer scientists, and theorists will appreciate this thorough and up-to-date treatment of sparse statistical modeling.
Written in simple language with relevant examples, Statistical Methods in Biology: Design and Analysis of Experiments and Regression is a practical and illustrative guide to the design of experiments and data analysis in the biological and agricultural sciences. The book presents statistical ideas in the context of biological and agricultural sciences to which they are being applied, drawing on relevant examples from the authors' experience.
Taking a practical and intuitive approach, the book only uses mathematical formulae to formalize the methods where necessary and appropriate. The text features extended discussions of examples that include real data sets arising from research. The authors analyze data in detail to illustrate the use of basic formulae for simple examples while using the GenStat(R) statistical package for more complex examples. Each chapter offers instructions on how to obtain the example analyses in GenStat and R.
By the time you reach the end of the book (and online material) you will have gained:
A clear appreciation of the importance of a statistical approach to the design of your experiments,
A sound understanding of the statistical methods used to analyse data obtained from designed experiments and of the regression approaches used to construct simple models to describe the observed response as a function of explanatory variables,
Sufficient knowledge of how to use one or more statistical packages to analyse data using the approaches described, and most importantly,
An appreciation of how to interpret the results of these statistical analyses in the context of the biological or agricultural science within which you are working.
The book concludes with a guide to practical design and data analysis. It gives you the understanding to better interact with consultant statisticians and to identify statistical approaches to add value to your scientific research.
Автор: J. Philip Miller Название: Essential Statistical Methods for Medical Statistics, ISBN: 0444537376 ISBN-13(EAN): 9780444537379 Издательство: Elsevier Science Рейтинг: Цена: 56940.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Addresses statistical challenges in epidemiological, biomedical, and pharmaceutical research. This book presents methods for assessing Biomarkers, analysis of competing risks. It offers clinical trials including sequential and group sequential, crossover designs, cluster randomized, and adaptive designs.
Автор: Guo Shenyang Y., Fraser Mark W. Название: Propensity Score Analysis: Statistical Methods and Applications ISBN: 1452235007 ISBN-13(EAN): 9781452235004 Издательство: Sage Publications Рейтинг: Цена: 120390.00 T Наличие на складе: Невозможна поставка. Описание: Provides readers with a systematic review of the origins, history, and statistical foundations of Propensity Score Analysis (PSA) and illustrates how it can be used for solving evaluation and causal-inference problems.
Автор: Josselin, Jean-michel Le Maux, Benoit Название: Statistical tools for program evaluation ISBN: 3319528262 ISBN-13(EAN): 9783319528267 Издательство: Springer Рейтинг: Цена: 102480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A self-contained presentation of the statistical tools for evaluating public programs, as advocated by many governments, the World Bank, the European Union and the Organization for Economic Cooperation and Development, the book takes a step-by-step approach and many numerical illustrations to equip readers to handle program evaluation statistics.
Автор: Pepe, Margaret Sullivan Название: The Statistical Evaluation of Medical Tests for Classification and Prediction ISBN: 0198565828 ISBN-13(EAN): 9780198565826 Издательство: Oxford Academ Рейтинг: Цена: 97150.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book describes statistical techniques for the design and evaluation of research studies on medical diagnostic tests, screening tests, biomarkers and new technologies for classification and prediction in medicine.
Автор: R. E. Burkard; T. B?nniger; G. Katzakidis; U. Deri Название: Assignment and Matching Problems: Solution Methods with FORTRAN-Programs ISBN: 3540102671 ISBN-13(EAN): 9783540102670 Издательство: Springer Рейтинг: Цена: 81050.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Dan Hirschberg; Gene Meyers Название: Combinatorial Pattern Matching ISBN: 3540612580 ISBN-13(EAN): 9783540612582 Издательство: Springer Рейтинг: Цена: 74530.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Comprising 26 papers presented at the 7th Annual Symposium on Combinatorial Pattern Matching (CPM), this work examines the importance of CPM, an area of algorithmics, in information retrieval, pattern recognition, compiling, data compression, program analysis, and molecular biology.
Автор: Kunihiko Ichikawa Название: Control System Design based on Exact Model Matching Techniques ISBN: 3540157727 ISBN-13(EAN): 9783540157724 Издательство: Springer Рейтинг: Цена: 95770.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Казахстан, 010000 г. Астана, проспект Туран 43/5, НП2 (офис 2) ТОО "Логобук" Тел:+7 707 857-29-98 ,+7(7172) 65-23-70 www.logobook.kz
