Автор: Mavrakakis Название: Modelling, Inference and Data Analysis ISBN: 158488939X ISBN-13(EAN): 9781584889397 Издательство: Taylor&Francis Рейтинг: Цена: 19906.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Covers aspects of probability, distribution theory and random processes that are fundamental to a proper understanding of inference. This book discusses the properties of estimators constructed from a random sample of ends, with sections on methods for estimating parameters in time series models.
Автор: H. Tong Название: Threshold Models in Non-linear Time Series Analysis ISBN: 0387909184 ISBN-13(EAN): 9780387909189 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In the last two years or so, I was most fortunate in being given opportunities of lecturing on a new methodology to a variety of audiences in Britain, China, Finland, France and Spain.
Автор: Tatarinova Tatiana, Schumitzky Alan Название: Nonlinear Mixture Models: A Bayesian Approach ISBN: 1848167563 ISBN-13(EAN): 9781848167568 Издательство: World Scientific Publishing Рейтинг: Цена: 14256.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Provides an introduction to the important subject of nonlinear mixture models from a Bayesian perspective. This title contains background material, a brief description of Markov chain theory, as well as novel algorithms and their applications.
Автор: Gobet Название: Monte-Carlo Methods & Stochastic Pr ISBN: 1498746225 ISBN-13(EAN): 9781498746229 Издательство: Taylor&Francis Рейтинг: Цена: 13779.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Developed from the author's course at the Ecole Polytechnique, Monte-Carlo Methods and Stochastic Processes: From Linear to Non-Linear focuses on the simulation of stochastic processes in continuous time and their link with partial differential equations (PDEs). It covers linear and nonlinear problems in biology, finance, geophysics, mechanics, chemistry, and other application areas. The text also thoroughly develops the problem of numerical integration and computation of expectation by the Monte-Carlo method.
The book begins with a history of Monte-Carlo methods and an overview of three typical Monte-Carlo problems: numerical integration and computation of expectation, simulation of complex distributions, and stochastic optimization. The remainder of the text is organized in three parts of progressive difficulty. The first part presents basic tools for stochastic simulation and analysis of algorithm convergence. The second part describes Monte-Carlo methods for the simulation of stochastic differential equations. The final part discusses the simulation of non-linear dynamics.
Автор: Nash, Ph.D. Название: Reliability Assessments ISBN: 1498719171 ISBN-13(EAN): 9781498719179 Издательство: Taylor&Francis Рейтинг: Цена: 24499.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This book provides engineers and scientists with a single source introduction to the concepts, models, and case studies for making credible reliability assessments. It satisfies the need for thorough discussions of several fundamental subjects.
Section I contains a comprehensive overview of assessing and assuring reliability that is followed by discussions of: - Concept of randomness and its relationship to chaos - Uses and limitations of the binomial and Poisson distributions - Relationship of the chi-square method and Poisson curves - Derivations and applications of the exponential, Weibull, and lognormal models - Examination of the human mortality bathtub curve as a template for components
Section II introduces the case study modeling of failure data and is followed by analyses of: - 5 sets of ideal Weibull, lognormal, and normal failure data - 83 sets of actual (real) failure data
The intent of the modeling was to find the best descriptions of the failures using statistical life models, principally the Weibull, lognormal, and normal models, for characterizing the failure probability distributions of the times-, cycles-, and miles-to-failure during laboratory or field testing. The statistical model providing the preferred characterization was determined empirically by choosing the two-parameter model that gave the best straight-line fit in the failure probability plots using a combination of visual inspection and three statistical goodness-of-fit (GoF) tests.
This book offers practical insight in dealing with single item reliability and illustrates the use of reliability methods to solve industry problems.
Описание: In their review of the "Bayesian analysis of simultaneous equation systems", Dr ze and Richard (1983) - hereafter DR - express the following viewpoint about the present state of development of the Bayesian full information analysis of such sys- tems i) the method allows "a flexible specification of the prior density, including well defined noninformative prior measures"; ii) it yields "exact finite sample posterior and predictive densities". However, they call for further developments so that these densities can be eval- uated through 'numerical methods, using an integrated software packa e. To that end, they recommend the use of a Monte Carlo technique, since van Dijk and Kloek (1980) have demonstrated that "the integrations can be done and how they are done". In this monograph, we explain how we contribute to achieve the developments suggested by Dr ze and Richard. A basic idea is to use known properties of the porterior density of the param- eters of the structural form to design the importance functions, i. e. approximations of the posterior density, that are needed for organizing the integrations.
Автор: Hocking Ronald R Название: Methods and Applications of Linear Models ISBN: 1118329503 ISBN-13(EAN): 9781118329504 Издательство: Wiley Рейтинг: Цена: 20109.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Praise for the Second Edition "An essential desktop reference book... it should definitely be on your bookshelf.
Автор: Fox John Название: Applied Regression Analysis and Generalized Linear Models ISBN: 1452205663 ISBN-13(EAN): 9781452205663 Издательство: Sage Publications Рейтинг: Цена: 25027.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Providing a modern treatment of regression analysis, linear models and closely related methods, this book introduces students to one of the most useful and widely used statistical tools for social research.
Название: Regression Modeling Strategies ISBN: 3319194240 ISBN-13(EAN): 9783319194240 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Most of the methods in this text apply to all regression models, but special emphasis is given to multiple regression using generalised least squares for longitudinal data, the binary logistic model, models for ordinal responses, parametric survival regression models and the Cox semi parametric survival model.
Автор: Frank E. Harrell , Jr. Название: Regression Modeling Strategies ISBN: 331933039X ISBN-13(EAN): 9783319330396 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Most of the methods in this text apply to all regression models, but special emphasis is given to multiple regression using generalised least squares for longitudinal data, the binary logistic model, models for ordinal responses, parametric survival regression models and the Cox semi parametric survival model.
Автор: Frank E. Harrell Название: Regression Modeling Strategies ISBN: 1441929185 ISBN-13(EAN): 9781441929181 Издательство: Springer Рейтинг: Цена: 12571.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: There are many books that are excellent sources of knowledge about individual stastical tools (survival models, general linear models, etc.), but the art of data analysis is about choosing and using multiple tools. In the words of Chatfield ..".students typically know the technical details of regressin for example, but not necessarily when and how to apply it. This argues the need for a better balance in the literature and in statistical teaching between techniques and problem solving strategies." Whether analyzing risk factors, adjusting for biases in observational studies, or developing predictive models, there are common problems that few regression texts address. For example, there are missing data in the majority of datasets one is likely to encounter (other than those used in textbooks ) but most regression texts do not include methods for dealing with such data effectively, and texts on missing data do not cover regression modeling.
Автор: Molloy Graham Название: Regression Analysis and Linear Models ISBN: 1635497051 ISBN-13(EAN): 9781635497052 Издательство: Неизвестно Цена: 24461.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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