Applied nonparametric statistical methods, Smeeton, Nigel Sprent, Peter (guy`s King & St. Thomas School Of Medicine, London, Uk)
Старое издание
Автор: Smeeton, Nigel C. Название: Applied Nonparametric Statistical Methods ISBN: 158488701X ISBN-13(EAN): 9781584887010 Издательство: Taylor&Francis Цена: 16078.00 р. Наличие на складе: Поставка под заказ.
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: 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: Dieter Rasch; Moti Lal Tiku Название: Robustness of Statistical Methods and Nonparametric Statistics ISBN: 9400965303 ISBN-13(EAN): 9789400965300 Издательство: Springer Рейтинг: Цена: 11173.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Chapter 1. The CUB models.- Chapter 2. Customer satisfaction heterogeneity.- Chapter 3. Ranking multivariate populations.- Chapter 4. Composite indicators and satisfaction profiles.- Chapter 5. Analyzing Survey Data Using Multivariate Rank-Based Inference
Автор: Patrice Bertail; Delphine Blanke; Pierre-Andr? Cor Название: Nonparametric Statistics ISBN: 3319969404 ISBN-13(EAN): 9783319969404 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume presents the latest advances and trends in nonparametric statistics, and gathers selected and peer-reviewed contributions from the 3rd Conference of the International Society for Nonparametric Statistics (ISNPS), held in Avignon, France on June 11-16, 2016. It covers a broad range of nonparametric statistical methods, from density estimation, survey sampling, resampling methods, kernel methods and extreme values, to statistical learning and classification, both in the standard i.i.d. case and for dependent data, including big data. The International Society for Nonparametric Statistics is uniquely global, and its international conferences are intended to foster the exchange of ideas and the latest advances among researchers from around the world, in cooperation with established statistical societies such as the Institute of Mathematical Statistics, the Bernoulli Society and the International Statistical Institute. The 3rd ISNPS conference in Avignon attracted more than 400 researchers from around the globe, and contributed to the further development and dissemination of nonparametric statistics knowledge.
Автор: Desu, M.M. , Raghavarao, D. Название: Nonparametric Statistical Methods For Complete and Censored Data ISBN: 0367394952 ISBN-13(EAN): 9780367394950 Издательство: Taylor&Francis Рейтинг: Цена: 9798.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Balancing the "cookbook" approach of some texts with the more mathematical approach of others, Nonparametric Statistical Methods for Complete and Censored Data introduces commonly used non-parametric methods for complete data and extends those methods to right censored data analysis. Whenever possible, the authors derive their methodology from the general theory of statistical inference and introduce the concepts intuitively for students with minimal backgrounds. Derivations and mathematical details are relegated to appendices at the end of each chapter, which allows students to easily proceed through each chapter without becoming bogged down in a lot of mathematics.
In addition to the nonparametric methods for analyzing complete and censored data, the book covers optimal linear rank statistics, clinical equivalence, analysis of block designs, and precedence tests. To make the material more accessible and practical, the authors use SAS programs to illustrate the various methods included.
Exercises in each chapter, SAS code, and a clear, accessible presentation make this an outstanding text for a one-semester senior or graduate-level course in nonparametric statistics for students in a variety of disciplines, from statistics and biostatistics to business, psychology, and the social scientists.
Prerequisites: Students will need a solid background in calculus and a two-semester course in mathematical statistics.
Автор: Gibbons, Jean Dickinson , Chakraborti, Subhabrata Название: Nonparametric Statistical Inference, Sixth Edition ISBN: 1138087440 ISBN-13(EAN): 9781138087446 Издательство: Taylor&Francis Рейтинг: Цена: 17609.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Since its first publication in 1971, Nonparametric Statistical Inference has been widely regarded as the source for learning about nonparametrics. The sixth edition carries on this tradition and incorporates computer solutions based on R.
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.
Автор: Kloke, John Название: Nonparametric Statistical Methods Using R ISBN: 0367739720 ISBN-13(EAN): 9780367739720 Издательство: Taylor&Francis Рейтинг: Цена: 6123.00 р. Наличие на складе: Поставка под заказ.
Автор: Gao, Jiti Название: Nonlinear Time Series ISBN: 0367389355 ISBN-13(EAN): 9780367389352 Издательство: Taylor&Francis Рейтинг: Цена: 9798.00 р. Наличие на складе: Поставка под заказ.
Описание:
Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric methods have received extensive attention in the economics and statistics communities over the past twenty years. Recent studies show that semiparametric methods and models may be applied to solve dimensionality reduction problems arising from using fully nonparametric models and methods. Answering the call for an up-to-date overview of the latest developments in the field, Nonlinear Time Series: Semiparametric and Nonparametric Methods focuses on various semiparametric methods in model estimation, specification testing, and selection of time series data.
After a brief introduction, the book examines semiparametric estimation and specification methods and then applies these approaches to a class of nonlinear continuous-time models with real-world data. It also assesses some newly proposed semiparametric estimation procedures for time series data with long-range dependence. Even though the book only deals with climatological and financial data, the estimation and specifications methods discussed can be applied to models with real-world data in many disciplines. This resource covers key methods in time series analysis and provides the necessary theoretical details. The latest applied finance and financial econometrics results and applications presented in the book enable researchers and graduate students to keep abreast of developments in the field.
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.
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