Автор: Petr N. Vabishchevich Название: Computational Technologies: Advanced Topics ISBN: 3110359944 ISBN-13(EAN): 9783110359947 Издательство: Walter de Gruyter Цена: 9288.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book discusses questions of numerical solutions of applied problems on parallel computing systems. Nowadays, engineering and scientific computations are carried out on parallel computing systems, which provide parallel data processing on a few computing nodes. In the development of up-to-date applied software, this feature of computers must be taken into account for the maximum efficient usage of their resources. In constructing computational algorithms, we should separate relatively independent subproblems in order to solve them on a single computing node.
Автор: Andrej V. Cherkaev; Robert Kohn Название: Topics in the Mathematical Modelling of Composite Materials ISBN: 1461273900 ISBN-13(EAN): 9781461273905 Издательство: Springer Рейтинг: Цена: 27950.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This work has implications for many physical problems involving optimal design, composite materials, and coherent phase transitions. Still other work was published in standard books or journals, but written in Russian or French.
Описание: 'Overall, the book is highly technical, including full mathematical proofs of the results stated. Potential readers are post-graduate students or researchers in Quantitative Risk Management willing to have a manual with the state-of-the-art on portfolio diversification and risk aggregation with heavy tails, including the fundamental theorems as well as collateral (but most useful) results on majorization and copula theory.'Quantitative Finance This book offers a unified approach to the study of crises, large fluctuations, dependence and contagion effects in economics and finance. It covers important topics in statistical modeling and estimation, which combine the notions of copulas and heavy tails -- two particularly valuable tools of today's research in economics, finance, econometrics and other fields -- in order to provide a new way of thinking about such vital problems as diversification of risk and propagation of crises through financial markets due to contagion phenomena, among others. The aim is to arm today's economists with a toolbox suited for analyzing multivariate data with many outliers and with arbitrary dependence patterns. The methods and topics discussed and used in the book include, in particular, majorization theory, heavy-tailed distributions and copula functions -- all applied to study robustness of economic, financial and statistical models, and estimation methods to heavy tails and dependence.
Описание: This volume contains a collection of survey papers in the areas of modelling, estimation and adaptive control of stochastic systems. It provides information on recent research and describes efforts to develop a systematic theory of identification and adaptive control.
Автор: Cherkaev Название: Topics in the Mathematical Modelling of Composite Materials ISBN: 3319971832 ISBN-13(EAN): 9783319971834 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Over the past several decades, we have witnessed a renaissance of theoretical work on the macroscopic behavior of microscopically heterogeneous materials. This work has implications for many physical problems involving optimal design, composite materials, and coherent phase transitions.
Автор: Andrej V. Cherkaev; Robert Kohn Название: Topics in the Mathematical Modelling of Composite Materials ISBN: 0817636625 ISBN-13(EAN): 9780817636623 Издательство: Springer Рейтинг: Цена: 33401.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A collection of research papers dealing with the macroscopic behaviour of microscopically hetergenous materials. The papers have been previously published in French or Russian as "hidden literature". This volume provides English translations of these works.
Описание: In order to assist a hospital in managing its resources and patients, modelling the length of stay is highly important. Recent health scholarship and practice has largely remained empirical, dwelling on primary data. This is critically important, first, because health planners generally rely on data to establish trends and patterns of disease burden at national or regional level. Secondly, epidemiologists depend on data to investigate possible risk factors of the disease. Yet the use of routine or secondary data has, in recent years, proved increasingly significant in such endeavours. Various units within the health systems collected such data primarily as part of the process for surveillance, monitoring and evaluation. Such data is sometimes periodically supplemented by population-based sample survey datasets. Thirdly, coupled with statistical tools, public health professionals are able to analyze health data and breathe life into what may turn out to be meaningless data. The main focus of this book is to present and showcase advanced modelling of routine or secondary survey data. Studies demonstrate that statistical literacy and knowledge are needed to understand health research outputs. The advent of user-friendly statistical packages combined with computing power and widespread availability of public health data resulted in more reported epidemiological studies in literature. However, analysis of secondary data, has some unique challenges. These are most widely reported health literature, so far has failed to recognize resulting in inappropriate analysis, and erroneous conclusions. This book presents the application of advanced statistical techniques to real examples emanating from routine or secondary survey data. These are essentially datasets in which the two editors have been involved, demonstrating how to tackle these challenges. Some of these challenges are: the complex sampling design of the surveys, the hierarchical nature of the data, the dependence of data at the sampled cluster and missing data among many more challenges. Using data from the Health Management Information System (HMIS), and Demographic and Health Survey (DHS), we provide various approaches and techniques of dealing with data complexity, how to handle correlated or clustered data. Each chapter presents an example code, which can be used to analyze similar data in R, Stata or SPSS. To make the book more concise, we have provided the codes on the books website. The book considers four main topics in the field of health sciences research: (i) structural equation modeling; (ii) spatial and spatio-temporal modeling; (iii) correlated or clustered copula modeling; and (iv) survival analysis. The book has potential to impact methodologists, including students undertaking Masters or Doctoral level programmes as well as other researchers seeking some related reference on quantitative analysis in public health or health sciences or other areas where data of similar nature would be applicable. Further the book can be a resource to public health professionals interested in quantitative approaches to answer questions of epidemiological nature. Each chapter starts with a motivating background, review of statistical methods, analysis and results, ending discussion and possible recommendations.
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