Автор: Larry Wasserman Название: All of Nonparametric Statistics ISBN: 1441920447 ISBN-13(EAN): 9781441920447 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: It covers a wide range of topics including the bootstrap, the nonparametric delta method, nonparametric regression, density estimation, orthogonal function methods, minimax estimation, nonparametric confidence sets, and wavelets.
Автор: Faghih, Nezameddin Bonyadi, Ebrahim Sarreshtehdari, Lida Название: Quality management and operations research ISBN: 0367744902 ISBN-13(EAN): 9780367744908 Издательство: Taylor&Francis Рейтинг: Цена: 11255.00 р. 16078.00-30% Наличие на складе: Есть (1 шт.) Описание: Offering a step-by-step approach for applying the Nonparametric Method with the Bayesian Approach to model complex relationships occurring in Reliability Engineering, Quality Management, and Operations Research, it also discusses survival and censored data, accelerated lifetime tests (issues in reliability data analysis), and R codes. This book uses the Nonparametric Bayesian approach in the fields of quality management and operations research. It presents a step-by-step approach for understanding and implementing these models, as well as includes R codes which can be used in any dataset. The book helps the readers to use statistical models in studying complex concepts and applying them to Operations Research, Industrial Engineering, Manufacturing Engineering, Computer Science, Quality and Reliability, Maintenance Planning and Operations Management.This book helps researchers, analysts, investigators, designers, producers, industrialists, entrepreneurs, and financial market decision makers, with finding the lifetime model of products, and for crucial decision-making in other markets.
Автор: Kolassa, John E. Название: An Introduction to nonparametric statistics ISBN: 0367194848 ISBN-13(EAN): 9780367194840 Издательство: Taylor&Francis Рейтинг: Цена: 14086.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents the theory and practice of non-parametric statistics, with an emphasis on motivating principals. The course is a combination of traditional rank based methods and more computationally-intensive topics like density estimation, kernel smoothers in regression, and robustness. The text is aimed at MS students.
Описание: An overview of the asymptotic theory of optimal nonparametric tests is presented in this book. It covers a wide range of topics: Neyman-Pearson and LeCam's theories of optimal tests, the theories of empirical processes and kernel estimators with extensions of their applications to the asymptotic behavior of tests for distribution functions, densities and curves of the nonparametric models defining the distributions of point processes and diffusions. With many new test statistics developed for smooth curves, the reliance on kernel estimators with bias corrections and the weak convergence of the estimators are useful to prove the asymptotic properties of the tests, extending the coverage to semiparametric models. They include tests built from continuously observed processes and observations with cumulative intervals.
Автор: Yakov Nikitin Название: Asymptotic Efficiency of Nonparametric Tests ISBN: 0521470293 ISBN-13(EAN): 9780521470292 Издательство: Cambridge Academ Рейтинг: Цена: 18058.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This monograph is the first unified treatment of an indispensable technique for comparing statistical tests, especially in nonparametric statistics. It presents powerful new methods to evaluate explicitly different kinds of efficiencies. Many Russian results are published here for the first time in English.
Автор: Jureckov?, Jana , Sen, Pranab , Picek, Jan Название: Methodology in Robust and Nonparametric Statistics ISBN: 0367381060 ISBN-13(EAN): 9780367381066 Издательство: Taylor&Francis Рейтинг: Цена: 9798.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Robust and nonparametric statistical methods have their foundation in fields ranging from agricultural science to astronomy, from biomedical sciences to the public health disciplines, and, more recently, in genomics, bioinformatics, and financial statistics. These disciplines are presently nourished by data mining and high-level computer-based algorithms, but to work actively with robust and nonparametric procedures, practitioners need to understand their background.
Explaining the underpinnings of robust methods and recent theoretical developments, Methodology in Robust and Nonparametric Statistics provides a profound mathematically rigorous explanation of the methodology of robust and nonparametric statistical procedures.
Thoroughly up-to-date, this book
Presents multivariate robust and nonparametric estimation with special emphasis on affine-equivariant procedures, followed by hypotheses testing and confidence sets
Keeps mathematical abstractions at bay while remaining largely theoretical
Provides a pool of basic mathematical tools used throughout the book in derivations of main results
The methodology presented, with due emphasis on asymptotics and interrelations, will pave the way for further developments on robust statistical procedures in more complex models. Using examples to illustrate the methods, the text highlights applications in the fields of biomedical science, bioinformatics, finance, and engineering. In addition, the authors provide exercises in the text.
Описание: Stationarity is a very general, qualitative assumption, that can be assessed on the basis of application specifics. It is thus a rather attractive assumption to base statistical analysis on, especially for problems for which less general qualitative assumptions, such as independence or finite memory, clearly fail. However, it has long been considered too general to be able to make statistical inference. One of the reasons for this is that rates of convergence, even of frequencies to the mean, are not available under this assumption alone. Recently, it has been shown that, while some natural and simple problems, such as homogeneity, are indeed provably impossible to solve if one only assumes that the data is stationary (or stationary ergodic), many others can be solved with rather simple and intuitive algorithms. The latter include clustering and change point estimation among others. In this volume I summarize these results. The emphasis is on asymptotic consistency, since this the strongest property one can obtain assuming stationarity alone. While for most of the problem for which a solution is found this solution is algorithmically realizable, the main objective in this area of research, the objective which is only partially attained, is to understand what is possible and what is not possible to do for stationary time series. The considered problems include homogeneity testing (the so-called two sample problem), clustering with respect to distribution, clustering with respect to independence, change point estimation, identity testing, and the general problem of composite hypotheses testing. For the latter problem, a topological criterion for the existence of a consistent test is presented. In addition, a number of open problems is presented.
Описание: Consists of 22 research papers in Probability and Statistics. This title includes topics such as nonparametric inference, nonparametric curve fitting, linear model theory, Bayesian nonparametrics, change point problems, time series analysis and asymptotic theory. It presents research in statistical theory.
Автор: Peter Sprent Название: Applied Nonparametric Statistical Methods ISBN: 940107044X ISBN-13(EAN): 9789401070447 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Understanding the rudiments helps one get better performance and makesdrivingsafer;appropriate gearchanges become a way to reduce engine stress, prolong engine life, improve fuel economy, minimize wear on brake linings.
Автор: Hettmansperger, Thomas P. Название: Robust Nonparametric Statistical Methods ISBN: 1439809089 ISBN-13(EAN): 9781439809082 Издательство: Taylor&Francis Рейтинг: Цена: 24499.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Kraska-MIller, M. Название: Nonparametric Statistics for Social and Behavioral Sciences ISBN: 0367379104 ISBN-13(EAN): 9780367379100 Издательство: Taylor&Francis Рейтинг: Цена: 9492.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Incorporating a hands-on pedagogical approach, Nonparametric Statistics for Social and Behavioral Sciences presents the concepts, principles, and methods used in performing many nonparametric procedures. It also demonstrates practical applications of the most common nonparametric procedures using IBM's SPSS software.
This text is the only current nonparametric book written specifically for students in the behavioral and social sciences. Emphasizing sound research designs, appropriate statistical analyses, and accurate interpretations of results, the text:
Explains a conceptual framework for each statistical procedure
Presents examples of relevant research problems, associated research questions, and hypotheses that precede each procedure
Details SPSS paths for conducting various analyses
Discusses the interpretations of statistical results and conclusions of the research
With minimal coverage of formulas, the book takes a nonmathematical approach to nonparametric data analysis procedures and shows students how they are used in research contexts. Each chapter includes examples, exercises, and SPSS screen shots illustrating steps of the statistical procedures and resulting output.
