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Nonparametric Statistics: 2nd Isnps, Cбdiz, June 2014, Cao Ricardo, Gonzбlez Manteiga Wenceslao, Romo Juan


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Автор: Cao Ricardo, Gonzбlez Manteiga Wenceslao, Romo Juan
Название:  Nonparametric Statistics: 2nd Isnps, Cбdiz, June 2014
ISBN: 9783319823881
Издательство: Springer
Классификация:


ISBN-10: 3319823884
Обложка/Формат: Paperback
Страницы: 224
Вес: 0.34 кг.
Дата издания: 15.06.2018
Серия: Springer proceedings in mathematics & statistics
Язык: English
Издание: Softcover reprint of
Иллюстрации: 19 illustrations, color; 21 illustrations, black and white; xi, 224 p. 40 illus., 19 illus. in color.
Размер: 23.39 x 15.60 x 1.27 cm
Читательская аудитория: General (us: trade)
Подзаголовок: 2nd isnps, cadiz, june 2014
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: S. Chakraborty and S. Datta: Robust Estimation in AFT Models and a Covariate Adjusted Mann-Whitney Statistic for Comparing Two Sojourn Times.- G. Benini, S. Sperlich and R. Theler: Varying Coefficient Models Revisited: An Econometric View.- J. Hidalgo and V. Dalla: Testing for Breaks in Regression Models with Dependent Data.- D. Bagkavos, P. N. Patil and A. T. A. Wood: A Numerical Study of the Power Function of a New Symmetry Test.- N. Markovich: Nonparametric Estimation of Heavy-Tailed Density by the Discrepancy Method.- S. Hudecova, M. Huskova and S. Meintanis: Change Detection in INARCH Time Series of Counts.- M. P. Espinosay, E. Ferreiraz and W. Stute: Discrimination, Binomials and Glass Ceiling Effects.- A. Antoniadis, X. Brossat, Y. Goude, J.-M. Poggi and V. Thouvenot: Automatic Component Selection in Additive Modeling of French National Electricity Load Forecasting.- S. Bonnini: Nonparametric Test on Process Capability.- E. Boj and T. Costa: Claim Reserving using Distance-Based Generalized Linear Models.- A. V. Dobrovidov: Regularization of Positive Signal Nonparametric Filtering in Multiplicative Observation Model.- V. Patrangenaru, K. D. Yao and R. Guo: Extrinsic Means and Antimeans.- G. Koshkin and V. Smagin: Kalman Filtering and Forecasting Algorithms with Use of Nonparametric Functional Estimators.- A. Meneses, S. Naya, I. Lopez-de-Ullibarri and J. Tarro-Saavedra: Nonparametric Method for Estimating the Distribution of Time to Failure of Engineering Materials.- G. J. Szekely and M. L. Rizzo: Partial Distance Correlation.



Автор: Larry Wasserman
Название: All of Nonparametric Statistics
ISBN: 1441920447 ISBN-13(EAN): 9781441920447
Издательство: Springer
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Цена: 15372.00 р.
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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.

Applied Nonparametric Statistics in Reliability

Автор: M. Luz G?miz; K. B. Kulasekera; Nikolaos Limnios;
Название: Applied Nonparametric Statistics in Reliability
ISBN: 1447126343 ISBN-13(EAN): 9781447126348
Издательство: Springer
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Цена: 23757.00 р.
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Описание: This volume focuses on the latest statistical methods used to estimate the performance measures of reliability systems that operate under different conditions. It includes numerous techniques such as nonparametric estimation and lifetime regression analysis.

Categorical and Nonparametric Data Analysis

Автор: Nussbaum E Michael
Название: Categorical and Nonparametric Data Analysis
ISBN: 1138787825 ISBN-13(EAN): 9781138787827
Издательство: Taylor&Francis
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Цена: 12248.00 р.
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Описание: Featuring in-depth coverage of categorical and nonparametric statistics, this book provides a conceptual framework for choosing the most appropriate type of test in various research scenarios. Class tested at the University of Nevada, the book's clear explanations of the underlying assumptions, computer simulations, and Exploring the Concept boxes help reduce reader anxiety. Problems inspired by actual studies provide meaningful illustrations of the techniques. The underlying assumptions of each test and the factors that impact validity and statistical power are reviewed so readers can explain their assumptions and how tests work in future publications. Numerous examples from psychology, education, and other social sciences demonstrate varied applications of the material. Basic statistics and probability are reviewed for those who need a refresher. Mathematical derivations are placed in optional appendices for those interested in this detailed coverage. Highlights include the following: Unique coverage of categorical and nonparametric statistics better prepares readers to select the best technique for their particular research project; however, some chapters can be omitted entirely if preferred. Step-by-step examples of each test help readers see how the material is applied in a variety of disciplines.  Although the book can be used with any program, examples of how to use the tests in SPSS and Excel foster conceptual understanding. Exploring the Concept boxes integrated throughout prompt students to review key material and draw links between the concepts to deepen understanding.  Problems in each chapter help readers test their understanding of the material.  Emphasis on selecting tests that maximize power helps readers avoid "marginally" significant results.  Website (www.routledge.com/9781138787827) features datasets for the book's examples and problems, and for the instructor, PowerPoint slides, sample syllabi, answers to the even-numbered problems, and Excel data sets for lecture purposes. Intended for individual or combined graduate or advanced undergraduate courses in categorical and nonparametric data analysis, cross-classified data analysis, advanced statistics and/or quantitative techniques taught in psychology, education, human development, sociology, political science, and other social and life sciences, the book also appeals to researchers in these disciplines. The nonparametric chapters can be deleted if preferred. Prerequisites include knowledge of t tests and ANOVA.

Nonparametric Statistics - A Step-by-Step Approach  2e

Автор: Corder
Название: Nonparametric Statistics - A Step-by-Step Approach 2e
ISBN: 1118840313 ISBN-13(EAN): 9781118840313
Издательство: Wiley
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Цена: 13139.00 р.
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Описание: a very useful resource for courses in nonparametric statistics in which the emphasis is on applications rather than on theory. It also deserves a place in libraries of all institutions where introductory statistics courses are taught.

All of Nonparametric Statistics

Автор: Wasserman
Название: All of Nonparametric Statistics
ISBN: 0387251456 ISBN-13(EAN): 9780387251455
Издательство: Springer
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Цена: 20962.00 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.

Applied Nonparametric Statistics in Reliability

Автор: G?miz
Название: Applied Nonparametric Statistics in Reliability
ISBN: 0857291173 ISBN-13(EAN): 9780857291172
Издательство: Springer
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Цена: 23757.00 р.
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Описание: Nonparametric statistics has probably become the leading methodology for researchers performing data analysis. It is nevertheless true that, whereas these methods have already proved highly effective in other applied areas of knowledge such as biostatistics or social sciences, nonparametric analyses in reliability currently form an interesting area of study that has not yet been fully explored. Applied Nonparametric Statistics in Reliability is focused on the use of modern statistical methods for the estimation of dependability measures of reliability systems that operate under different conditions. The scope of the book includes: smooth estimation of the reliability function and hazard rate of non-repairable systems; study of stochastic processes for modelling the time evolution of systems when imperfect repairs are performed; nonparametric analysis of discrete and continuous time semi-Markov processes; isotonic regression analysis of the structure function of a reliability system, and lifetime regression analysis. Besides the explanation of the mathematical background, several numerical computations or simulations are presented as illustrative examples. The corresponding computer-based methods have been implemented using R and MATLAB®. A concrete modelling scheme is chosen for each practical situation and, in consequence, a nonparametric inference procedure is conducted. Applied Nonparametric Statistics in Reliability will serve the practical needs of scientists (statisticians and engineers) working on applied reliability subjects.

Nonparametric Statistics: 4th Isnps, Salerno, Italy, June 2018

Автор: La Rocca Michele, Liseo Brunero, Salmaso Luigi
Название: Nonparametric Statistics: 4th Isnps, Salerno, Italy, June 2018
ISBN: 3030573052 ISBN-13(EAN): 9783030573058
Издательство: Springer
Цена: 27950.00 р.
Наличие на складе: Поставка под заказ.

Описание: This book is intended for periodontal residents and practicing periodontists who wish to incorporate the principles of moderate sedation into daily practice. Comprehensive airway management and rescue skills are then documented in detail so that the patient may be properly managed in the event that the sedation progresses beyond the intended level.

An Introduction to nonparametric statistics

Автор: Kolassa, John E.
Название: An Introduction to nonparametric statistics
ISBN: 0367194848 ISBN-13(EAN): 9780367194840
Издательство: Taylor&Francis
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Цена: 14086.00 р.
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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.

Practical Nonparametric Statistics

Автор: Conover, W.J.
Название: Practical Nonparametric Statistics
ISBN: 0471160687 ISBN-13(EAN): 9780471160687
Издательство: Wiley
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Цена: 36741.00 р.
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Описание: This highly-regarded text serves as a quick reference book which offers clear, concise instructions on how and when to use the most popular nonparametric procedures.

Nonparametric Statistics for Applied Research

Название: Nonparametric Statistics for Applied Research
ISBN: 1461490405 ISBN-13(EAN): 9781461490401
Издательство: Springer
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Цена: 8384.00 р.
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Описание:

​​Non-parametric methods are widely used for studying populations that take on a ranked order (such as movie reviews receiving one to four stars). The use of non-parametric methods may be necessary when data have a ranking but no clear numerical interpretation, such as when assessing preferences. In terms of levels of measurement, non-parametric methods result in ordinal data. As non-parametric methods make fewer assumptions, their applicability is much wider than the corresponding parametric methods. In particular, they may be applied in situations where less is known about the application in question. Also, due to the reliance on fewer assumptions, non-parametric methods are more robust. Non-parametric methods have many popular applications, and are widely used in research in the fields of the behavioral sciences and biomedicine.

This is a textbook on non-parametric statistics for applied research. The authors propose to use a realistic yet mostly fictional situation and series of dialogues to illustrate in detail the statistical processes required to complete data analysis. This book draws on a readers existing elementary knowledge of statistical analyses to broaden his/her research capabilities. The material within the book is covered in such a way that someone with a very limited knowledge of statistics would be able to read and understand the concepts detailed in the text.

The "real world" scenario to be presented involves a multidisciplinary team of behavioral, medical, crime analysis, and policy analysis professionals work together to answer specific empirical questions regarding real-world applied problems. The reader is introduced to the team and the data set, and through the course of the text follows the team as they progress through the decision making process of narrowing the data and the research questions to answer the applied problem. In this way, abstract statistical concepts are translated into concrete and specific language.

This text uses one data set from which all examples are taken. This is radically different from other statistics books which provide a varied array of examples and data sets. Using only one data set facilitates reader-directed teaching and learning by providing multiple research questions which are integrated rather than using disparate examples and completely unrelated research questions and data.


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