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: 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.
Автор: Corder Название: Nonparametric Statistics - A Step-by-Step Approach 2e ISBN: 1118840313 ISBN-13(EAN): 9781118840313 Издательство: Wiley Рейтинг: Цена: 13139.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
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.
Автор: Wasserman Название: All of Nonparametric Statistics ISBN: 0387251456 ISBN-13(EAN): 9780387251455 Издательство: Springer Рейтинг: 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.
Автор: Mayer Alvo; Philip L. H. Yu Название: A Parametric Approach to Nonparametric Statistics ISBN: 3030068048 ISBN-13(EAN): 9783030068042 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book demonstrates that nonparametric statistics can be taught from a parametric point of view. As a result, one can exploit various parametric tools such as the use of the likelihood function, penalized likelihood and score functions to not only derive well-known tests but to also go beyond and make use of Bayesian methods to analyze ranking data. The book bridges the gap between parametric and nonparametric statistics and presents the best practices of the former while enjoying the robustness properties of the latter.This book can be used in a graduate course in nonparametrics, with parts being accessible to senior undergraduates. In addition, the book will be of wide interest to statisticians and researchers in applied fields.
Автор: Bhattacharya Название: Nonparametric Inference on Manifolds ISBN: 1107484316 ISBN-13(EAN): 9781107484313 Издательство: Cambridge Academ Рейтинг: Цена: 6019.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Ideal for statisticians, this book will also interest probabilists, mathematicians, computer scientists, and morphometricians with mathematical training. It presents a systematic introduction to a general nonparametric theory of statistics on manifolds, with emphasis on manifolds of shapes. The theory has important applications in medical diagnostics, image analysis and machine vision.
Автор: D. Bosq Название: Nonparametric Statistics for Stochastic Processes ISBN: 0387985905 ISBN-13(EAN): 9780387985909 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Deals with the theory and applications of nonparametic functional estimation and prediction. This book provides an overview of inequalities and limit theorems for strong mixing processes. It studies density and regression estimation in discrete time. It presents the special rates of convergence which appear in continuous time.
Автор: Nussbaum E Michael Название: Categorical and Nonparametric Data Analysis ISBN: 1138787825 ISBN-13(EAN): 9781138787827 Издательство: Taylor&Francis Рейтинг: Цена: 12248.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Описание: 1 Nonparametric Statistics for the Biological Sciences1.1 Purpose of This Lesson 1.2 Data Types 1.2.1 Nominal Data 1.2.2 Ordinal Data1.2.3 Interval Data and Ratio Data1.3 Graphical Presentation of Populations1.3.1 Samples that Exhibit Normal Distribution1.3.2 Samples that Fail to Exhibit Normal Distribution1.4 R and Nonparametric Analyses1.4.1 Precision of Scales: Ordinal v Interval1.4.2 Deviation from Normal Distribution1.4.3 Sample Size: Number of Subjects for Each Breakout Group1.5 Definition of Nonparametric Analysis1.6 Statistical Tests and Graphics Associated with Distribution Patterns1.7 Prepare to Exit, Save, and Later Retrieve This R Session 2 Sign Test2.1 Background on This Lesson2.1.1 Description of the Data2.1.2 Null Hypothesis (Ho)2.2 Data Import of a .csv Spreadsheet-Type Data File into R2.3 Organize the Data and Display the Code Book2.4 Conduct a Visual Data Check2.5 Descriptive Analysis of the Data2.6 Conduct the Statistical Analysis2.7 Summary 2.8 Prepare to Exit, Save, and Later Retrieve This R Session 3 Chi-Square3.1 Background on This Lesson3.1.1 Description of the Data3.1.2 Null Hypothesis (Ho)3.2 Data Import of a .csv Spreadsheet-Type Data File into R3.3 Organize the Data and Display the Code Book3.4 Conduct a Visual Data Check3.5 Descriptive Analysis of the Data3.6 Conduct the Statistical Analysis3.7 Summary3.8 Addendum: Calculate the Chi-Square Statistic from Contingency Tables3.9 Prepare to Exit, Save, and Later Retrieve This R Session 4 Mann-Whitney U Test4.1 Background on This Lesson4.1.1 Description of the Data4.1.2 Null Hypothesis (Ho)4.2 Data Import of a .csv Spreadsheet-Type Data File into R4.3 Organize the Data and Display the Code Book4.4 Conduct a Visual Data Check4.5 Descriptive Analysis of the Data4.6 Conduct the Statistical Analysis4.7 Summary4.8 Addendum: Stacked Data v Unstacked Data4.9 Prepare to Exit, Save, and Later Retrieve This R Session 5 Wilcoxon Matched-Pairs Signed-Ranks Test5.1 Background on This Lesson5.1.1 Description of the Data5.1.2 Null Hypothesis (Ho)5.2 Data Import of a .csv Spreadsheet-Type Data File into R5.3 Organize the Data and Display the Code Book5.4 Conduct a Visual Data Check5.5 Descriptive Analysis of the Data5.6 Conduct the Statistical Analysis5.7 SummaryTest5.9 Addendum 2: Similar Functions from Different Packages5.10 Addendum 3: Nonparamteric v Parametric Confirmation of Outcomes5.11 Prepare to Exit, Save, and Later Retrieve This R Session 6 Kruskal-Wallis H-Test for Oneway Analysis of Variance (ANOVA) by Ranks6.1 Background on This Lesson6.1.1 Description of the Data6.1.2 Null Hypothesis (Ho)6.2 Data Import of a .csv Spreadsheet-Type Data File into R6.3 Organize the Data and Display the Code Book6.4 Conduct a Visual Data Check6.5 Descriptive Analysis of the Data6.6 Conduct the Statistical Analysis6.7 Summary6.8 Addendum: Comparison of Kruskal-Wallis Test Differences by Breakout Group6.9 Prepare to Exit, Save, and Later Retrieve This R Session 7 Friedman Two Way A
Автор: Cao Ricardo, Gonzбlez Manteiga Wenceslao, Romo Juan Название: Nonparametric Statistics: 2nd Isnps, Cбdiz, June 2014 ISBN: 3319823884 ISBN-13(EAN): 9783319823881 Издательство: Springer Рейтинг: Цена: 26194.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Groeneboom Название: Nonparametric Estimation under Shape Constraints ISBN: 0521864011 ISBN-13(EAN): 9780521864015 Издательство: Cambridge Academ Рейтинг: Цена: 11880.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book treats the latest developments in the theory of order-restricted inference, with special attention to nonparametric methods and algorithmic aspects. Each chapter ends with a set of exercises of varying difficulty. The theory is illustrated with the analysis of real-life data, which are mostly medical in nature.
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