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Parallel Scientific Computing and Optimization, Raimondas Ciegis; David Henty; Bo K?gstr?m; Julius


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Автор: Raimondas Ciegis; David Henty; Bo K?gstr?m; Julius
Название:  Parallel Scientific Computing and Optimization
ISBN: 9780387097060
Издательство: Springer
Классификация:





ISBN-10: 0387097066
Обложка/Формат: Hardback
Страницы: 300
Вес: 0.60 кг.
Дата издания: 2008
Серия: Springer Optimization and Its Applications
Язык: English
Издание: 2009 ed.
Иллюстрации: 60 black & white illustrations, 10 black & white t
Размер: 234 x 156 x 18
Читательская аудитория: Professional & vocational
Подзаголовок: Advances and applications
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Introduces the developments in the construction, analysis, and implementation of parallel computing algorithms. This book includes construction and analysis of parallel algorithms for linear algebra and optimization problems. It covers different aspects of parallel architectures, including distributed memory computers with multicore processors.

Data Analysis Using Stata, Third Edition

Автор: Kohler
Название: Data Analysis Using Stata, Third Edition
ISBN: 1597181102 ISBN-13(EAN): 9781597181105
Издательство: Taylor&Francis
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Цена: 74510.00 T
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Описание:

Data Analysis Using Stata, Third Edition is a comprehensive introduction to both statistical methods and Stata. Beginners will learn the logic of data analysis and interpretation and easily become self-sufficient data analysts. Readers already familiar with Stata will find it an enjoyable resource for picking up new tips and tricks.

The book is written as a self-study tutorial and organized around examples. It interactively introduces statistical techniques such as data exploration, description, and regression techniques for continuous and binary dependent variables. Step by step, readers move through the entire process of data analysis and in doing so learn the principles of Stata, data manipulation, graphical representation, and programs to automate repetitive tasks. This third edition includes advanced topics, such as factor-variables notation, average marginal effects, standard errors in complex survey, and multiple imputation in a way, that beginners of both data analysis and Stata can understand.

Using data from a longitudinal study of private households, the authors provide examples from the social sciences that are relatable to researchers from all disciplines. The examples emphasize good statistical practice and reproducible research. Readers are encouraged to download the companion package of datasets to replicate the examples as they work through the book. Each chapter ends with exercises to consolidate acquired skills.


Introduction to Time Series Using Stata

Автор: Becketti
Название: Introduction to Time Series Using Stata
ISBN: 1597181323 ISBN-13(EAN): 9781597181327
Издательство: Taylor&Francis
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Цена: 75530.00 T
Наличие на складе: Невозможна поставка.
Описание: Recent decades have witnessed explosive growth in new and powerful tools for timeseries analysis. These innovations have overturned older approaches to forecasting, macroeconomic policy analysis, the study of productivity and long-run economic growth, and the trading of financial assets. Familiarity with these new tools on time series is an essential skill for statisticians, econometricians, and applied researchers. Introduction to Time Series Using Stata provides a step-by-step guide to essential timeseries techniques—from the incredibly simple to the quite complex—and, at the same time, demonstrates how these techniques can be applied in the Stata statistical package. The emphasis is on an understanding of the intuition underlying theoretical innovations and an ability to apply them. Real-world examples illustrate the application of each concept as it is introduced, and care is taken to highlight the pitfalls, as well as the power, of each new tool. Sean Becketti is a financial industry veteran with three decades of experience in academics, government, and private industry. Over the last two decades, Becketti has led proprietary research teams at several leading financial firms, responsible for the models underlying the valuation, hedging, and relative value analysis of some of the largest fixed-income portfolios in the world.

Combinatorial Optimization (algorithms and Combinatorics 21) 5th ed.

Автор: Korte, Bernhard, Vygen, Jens
Название: Combinatorial Optimization (algorithms and Combinatorics 21) 5th ed.
ISBN: 3642244874 ISBN-13(EAN): 9783642244872
Издательство: Springer
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Цена: 60510.00 T
Наличие на складе: Невозможна поставка.
Описание: This comprehensive textbook on combinatorial optimization places special emphasis on theoretical results and algorithms with provably good performance, in contrast to heuristics. It is based on numerous courses on combinatorial optimization and specialized topics, mostly at graduate level. This book reviews the fundamentals, covers the classical topics (paths, flows, matching, matroids, NP-completeness, approximation algorithms) in detail, and proceeds to advanced and recent topics, some of which have not appeared in a textbook before. Throughout, it contains complete but concise proofs, and also provides numerous exercises and references. This fifth edition has again been updated, revised, and significantly extended, with more than 60 new exercises and new material on various topics, including Cayley's formula, blocking flows, faster b-matching separation, multidimensional knapsack, multicommodity max-flow min-cut ratio, and sparsest cut. Thus, this book represents the state of the art of combinatorial optimization.

Introduction to Probability with Mathematica, Second Edition

Автор: Hastings
Название: Introduction to Probability with Mathematica, Second Edition
ISBN: 1420079387 ISBN-13(EAN): 9781420079388
Издательство: Taylor&Francis
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Цена: 183750.00 T
Наличие на складе: Невозможна поставка.
Описание: Updated to conform to Mathematica (R) 7.0, this second edition shows how to easily create simulations from templates and solve problems using Mathematica. Along with new sections on order statistics, transformations of multivariate normal random variables, and Brownian motion, this edition offers an expanded section on

V-Invex Functions and Vector Optimization

Автор: Shashi K. Mishra; Shouyang Wang; Kin Keung Lai
Название: V-Invex Functions and Vector Optimization
ISBN: 1441945288 ISBN-13(EAN): 9781441945280
Издательство: Springer
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Цена: 107130.00 T
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Описание: This volume summarizes and synthesizes an aspect of research work that has been done in the area of Generalized Convexity over the past few decades. The authors integrate related research into the book and demonstrate the wide context from which the area has grown and continues to grow.

Generalized Convexity and Vector Optimization

Автор: Shashi K. Mishra; Shouyang Wang; Kin Keung Lai
Название: Generalized Convexity and Vector Optimization
ISBN: 3642099300 ISBN-13(EAN): 9783642099304
Издательство: Springer
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Цена: 153720.00 T
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Описание: This book discusses the Kuhn-Tucker Optimality, Karush-Kuhn-Tucker Necessary and Sufficient Optimality Conditions in presence of various types of generalized convexity assumptions. It details the present state of knowledge on research done in this area.

Stochastic Optimization Methods in Finance and Energy

Автор: Marida Bertocchi; Giorgio Consigli; Michael A. H.
Название: Stochastic Optimization Methods in Finance and Energy
ISBN: 1461430275 ISBN-13(EAN): 9781461430278
Издательство: Springer
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Цена: 204040.00 T
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Описание: This book presents contributions dedicated to applied problems in the financial and energy sectors that have been formulated and solved in a stochastic optimization framework. Coverage also extends to theoretical and computational issues.

Clinical Trial Optimization using R

Название: Clinical Trial Optimization using R
ISBN: 149873507X ISBN-13(EAN): 9781498735070
Издательство: Taylor&Francis
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Цена: 107190.00 T
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Описание:

Clinical Trial Optimization Using R explores a unified and broadly applicable framework for optimizing decision making and strategy selection in clinical development, through a series of examples and case studies. It provides the clinical researcher with a powerful evaluation paradigm, as well as supportive R tools, to evaluate and select among simultaneous competing designs or analysis options. It is applicable broadly to statisticians and other quantitative clinical trialists, who have an interest in optimizing clinical trials, clinical trial programs, or associated analytics and decision making.

This book presents in depth the Clinical Scenario Evaluation (CSE) framework, and discusses optimization strategies, including the quantitative assessment of tradeoffs. A variety of common development challenges are evaluated as case studies, and used to show how this framework both simplifies and optimizes strategy selection. Specific settings include optimizing adaptive designs, multiplicity and subgroup analysis strategies, and overall development decision-making criteria around Go/No-Go. After this book, the reader will be equipped to extend the CSE framework to their particular development challenges as well.


Mathematical Optimization and Economic Analysis

Автор: Mikul?s Lupt?cik
Название: Mathematical Optimization and Economic Analysis
ISBN: 146142464X ISBN-13(EAN): 9781461424642
Издательство: Springer
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Цена: 135090.00 T
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Описание: This monograph is a self-contained introduction to the optimization techniques used in economic modeling such as mathematical programming and data envelopment analysis. This book demonstrates the usefulness of these mathematical tools in quantitative and qualitative economic analysis.

Elementary Stochastic Calculus, with Finance in View

Автор: Mikosch, Thomas
Название: Elementary Stochastic Calculus, with Finance in View
ISBN: 9810235437 ISBN-13(EAN): 9789810235437
Издательство: World Scientific Publishing
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Цена: 50690.00 T
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Описание: An elementary introduction to modelling with Ito integral or stochastic differential equations, without burdening the reader with a great deal of measure theory. Applications are taken from stochastic finance. In particular, the Black-Scholes option pricing formula is derived.


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