Empirical Direction in Design and Analysis, Anderson, Norman H.
Автор: Senn, Stephen Название: Dicing with death ISBN: 1108999867 ISBN-13(EAN): 9781108999861 Издательство: Cambridge Academ Рейтинг: Цена: 3166.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: From measles to malaria, from clinical trials to COVID and from life tables to the law, the second edition of Dicing with Death explains how the vital decisions we have to make both individually and collectively can be informed and improved by good data, statistical reasoning and analysis.
Автор: Thomas A. Garrity Название: All the Math You Missed ISBN: 1009009192 ISBN-13(EAN): 9781009009195 Издательство: Cambridge Academ Рейтинг: Цена: 3960.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The second edition of this bestselling book provides an overview of the key topics in undergraduate mathematics, allowing beginning graduate students to fill in any gaps in their knowledge. With numerous examples, exercises and suggestions for further reading, it is a must-have for anyone looking to learn some serious mathematics quickly.
Автор: Hamilton, James Название: Time Series Analysis ISBN: 0691042896 ISBN-13(EAN): 9780691042893 Издательство: Wiley Рейтинг: Цена: 11088.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A graduate-level text which describes the recent dramatic changes that have taken place in the way that researchers analyze economic and financial time series. It explores such important innovations as vector regression, nonlinear time series models and the generalized methods of moments.
Автор: Anderson, Norman H. Название: Empirical Direction in Design and Analysis ISBN: 0805840834 ISBN-13(EAN): 9780805840834 Издательство: Taylor&Francis Рейтинг: Цена: 7654.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: It provides a solid foundation for the optimization and reconstruction of traffic theoretical models, urban traffic planning, management and decision-making.This book helps traffic engineering researchers, traffic engineering technicians and traffic industry managers understand the difficulties and challenges faced by transportation big data.
Автор: Bickel, David R. Название: Genomics Data Analysis ISBN: 1032475285 ISBN-13(EAN): 9781032475288 Издательство: Taylor&Francis Рейтинг: Цена: 3367.00 р. Наличие на складе: Поставка под заказ.
Автор: Yang, Yang Название: Age-Period-Cohort Analysis ISBN: 1466507527 ISBN-13(EAN): 9781466507524 Издательство: Taylor&Francis Рейтинг: Цена: 17609.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Researchers and students who use empirical investigation in their work must go through the process of selecting statistical methods for analyses, and they are often challenged to justify these selections.
Название: Empirical Likelihood Method in Survival Analysis ISBN: 1466554924 ISBN-13(EAN): 9781466554924 Издательство: Taylor&Francis Рейтинг: Цена: 13779.00 р. Наличие на складе: Поставка под заказ.
Автор: Pardo Scott Название: Empirical Modeling and Data Analysis for Engineers and Appli ISBN: 3319327674 ISBN-13(EAN): 9783319327679 Издательство: Springer Рейтинг: Цена: 9362.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This textbook teaches advanced undergraduate and first-year graduate students in Engineering and Applied Sciences to gather and analyze empirical observations (data) in order to aid in making design decisions.
While science is about discovery, the primary paradigm of engineering and 'applied science' is design. Scientists are in the discovery business and want, in general, to understand the natural world rather than to alter it. In contrast, engineers and applied scientists design products, processes, and solutions to problems.
That said, statistics, as a discipline, is mostly oriented toward the discovery paradigm. Young engineers come out of their degree programs having taken courses such as 'Statistics for Engineers and Scientists' without any clear idea as to how they can use statistical methods to help them design products or processes. Many seem to think that statistics is only useful for demonstrating that a device or process actually does what it was designed to do. Statistics courses emphasize creating predictive or classification models - predicting nature or classifying individuals, and statistics is often used to prove or disprove phenomena as opposed to aiding in the design of a product or process. In industry however, Chemical Engineers use designed experiments to optimize petroleum extraction; Manufacturing Engineers use experimental data to optimize machine operation; Industrial Engineers might use data to determine the optimal number of operators required in a manual assembly process. This text teaches engineering and applied science students to incorporate empirical investigation into such design processes.
Much of the discussion in this book is about models, not whether the models truly represent reality but whether they adequately represent reality with respect to the problems at hand; many ideas focus on how to gather data in the most efficient way possible to construct adequate models.Includes chapters on subjects not often seen together in a single text (e.g., measurement systems, mixture experiments, logistic regression, Taguchi methods, simulation)Techniques and concepts introduced present a wide variety of design situations familiar to engineers and applied scientists and inspire incorporation of experimentation and empirical investigation into the design process.Software is integrally linked to statistical analyses with fully worked examples in each chapter; fully worked using several packages: SAS, R, JMP, Minitab, and MS Excel - also including discussion questions at the end of each chapter.
The fundamental learning objective of this textbook is for the reader to understand how experimental data can be used to make design decisions and to be familiar with the most common types of experimental designs and analysis methods.
Автор: Florian Jacob Название: Risk Estimation on High Frequency Financial Data ISBN: 3658093889 ISBN-13(EAN): 9783658093884 Издательство: Springer Рейтинг: Цена: 7836.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: By studying the ability of the Normal Tempered Stable (NTS) model to fit thestatistical features of intraday data at a 5 min sampling frequency, Florian Jacobs extends the research on high frequency data as well as the appliance of tempered stable models.
Автор: Zhou, Mai Название: Empirical likelihood method in survival analysis ISBN: 0367377578 ISBN-13(EAN): 9780367377571 Издательство: Taylor&Francis Рейтинг: Цена: 9798.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Add the Empirical Likelihood to Your Nonparametric Toolbox
Empirical Likelihood Method in Survival Analysis explains how to use the empirical likelihood method for right censored survival data. The author uses R for calculating empirical likelihood and includes many worked out examples with the associated R code. The datasets and code are available for download on his website and CRAN.
The book focuses on all the standard survival analysis topics treated with empirical likelihood, including hazard functions, cumulative distribution functions, analysis of the Cox model, and computation of empirical likelihood for censored data. It also covers semi-parametric accelerated failure time models, the optimality of confidence regions derived from empirical likelihood or plug-in empirical likelihood ratio tests, and several empirical likelihood confidence band results.
While survival analysis is a classic area of statistical study, the empirical likelihood methodology has only recently been developed. Until now, just one book was available on empirical likelihood and most statistical software did not include empirical likelihood procedures. Addressing this shortfall, this book provides the functions to calculate the empirical likelihood ratio in survival analysis as well as functions related to the empirical likelihood analysis of the Cox regression model and other hazard regression models.
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