Recent Developments in Nonparametric Inference and Probability
| Author | : |
| Publisher | : IMS |
| Total Pages | : 252 |
| Release | : 2006 |
| Genre | : Nonparametric statistics |
| ISBN | : 9780940600669 |
Recent Developments In Nonparametric Inference And Probability
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Nonparametric Statistical Inference
| Author | : Jean Dickinson Gibbons |
| Publisher | : CRC Press |
| Total Pages | : 695 |
| Release | : 2020-12-21 |
| Genre | : Mathematics |
| ISBN | : 135161617X |
Praise for previous editions: "... a classic with a long history." – Statistical Papers "The fact that the first edition of this book was published in 1971 ... [is] testimony to the book’s success over a long period." – ISI Short Book Reviews "... one of the best books available for a theory course on nonparametric statistics. ... very well written and organized ... recommended for teachers and graduate students." – Biometrics "... There is no competitor for this book and its comprehensive development and application of nonparametric methods. Users of one of the earlier editions should certainly consider upgrading to this new edition." – Technometrics "... Useful to students and research workers ... a good textbook for a beginning graduate-level course in nonparametric statistics." – Journal of the American Statistical Association 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. Features Covers the most commonly used nonparametric procedures States the assumptions, develops the theory behind the procedures, and illustrates the techniques using realistic examples from the social, behavioral, and life sciences Presents tests of hypotheses, confidence-interval estimation, sample size determination, power, and comparisons of competing procedures Includes an Appendix of user-friendly tables needed for solutions to all data-oriented examples Gives examples of computer applications based on R, MINITAB, STATXACT, and SAS Lists over 100 new references Nonparametric Statistical Inference, Sixth Edition, has been thoroughly revised and rewritten to make it more readable and reader-friendly. All of the R solutions are new and make this book much more useful for applications in modern times. It has been updated throughout and contains 100 new citations, including some of the most recent, to make it more current and useful for researchers.
Recent Developments in Nonparametric Inference and Probability
| Author | : |
| Publisher | : |
| Total Pages | : 231 |
| Release | : 2008 |
| Genre | : Nonparametric statistics |
| ISBN | : |
This e-book is the product of Project Euclid and its mission to advance scholarly communication in the field of theoretical and applied mathematics and statistics. Project Euclid was developed and deployed by the Cornell University Library and is jointly managed by Cornell and the Duke University Press.
Nonparametric Statistical Inference
| Author | : Jean Dickinson Gibbons |
| Publisher | : CRC Press |
| Total Pages | : 435 |
| Release | : 2020-12-22 |
| Genre | : Mathematics |
| ISBN | : 1351616161 |
Praise for previous editions: "... a classic with a long history." – Statistical Papers "The fact that the first edition of this book was published in 1971 ... [is] testimony to the book’s success over a long period." – ISI Short Book Reviews "... one of the best books available for a theory course on nonparametric statistics. ... very well written and organized ... recommended for teachers and graduate students." – Biometrics "... There is no competitor for this book and its comprehensive development and application of nonparametric methods. Users of one of the earlier editions should certainly consider upgrading to this new edition." – Technometrics "... Useful to students and research workers ... a good textbook for a beginning graduate-level course in nonparametric statistics." – Journal of the American Statistical Association 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. Features Covers the most commonly used nonparametric procedures States the assumptions, develops the theory behind the procedures, and illustrates the techniques using realistic examples from the social, behavioral, and life sciences Presents tests of hypotheses, confidence-interval estimation, sample size determination, power, and comparisons of competing procedures Includes an Appendix of user-friendly tables needed for solutions to all data-oriented examples Gives examples of computer applications based on R, MINITAB, STATXACT, and SAS Lists over 100 new references Nonparametric Statistical Inference, Sixth Edition, has been thoroughly revised and rewritten to make it more readable and reader-friendly. All of the R solutions are new and make this book much more useful for applications in modern times. It has been updated throughout and contains 100 new citations, including some of the most recent, to make it more current and useful for researchers.
Recent Developments in Nonparametric Inference and Probability
| Author | : Jiayang Sun |
| Publisher | : |
| Total Pages | : 248 |
| Release | : 2006 |
| Genre | : Nonparametric statistics |
| ISBN | : |
Nonparametric Inference
| Author | : Z. Govindarajulu |
| Publisher | : World Scientific Publishing Company Incorporated |
| Total Pages | : 669 |
| Release | : 2007-01-01 |
| Genre | : Mathematics |
| ISBN | : 981270034X |
This book provides a solid foundation on nonparametric inference for students taking a graduate course in nonparametric statistics and serves as an easily accessible source for researchers in the area. With the exception of some sections requiring familiarity with measure theory, readers with an advanced calculus background will be comfortable with the material.
Recent Developments in Statistical Inference and Data Analysis
| Author | : Kameo Matsushita |
| Publisher | : North Holland |
| Total Pages | : 384 |
| Release | : 1980 |
| Genre | : Mathematics |
| ISBN | : |
Enlarged mathematical representation for stochastic phenomena; Specification of statistical models by sufficiency;A modification of Brown's technique for proving inadmissibility; Estimating linear functional relationships; An empirical bayes approach to outliers: shifted mean case; Exploratory data analysis when data are matrices; Spatial patterns of territories; On the distribution of the likelihood ratio criterion for a covariance matrix; Some statistical methods of estimating the size of an animal population; Analysis of sentence structure by reordering processes; On the estimators for estimating variance of a normal distribution; Conditionality and maximum-likelihood estimation; Empirical bayes two-way decision in the case of discrete distributions; On an autoregressive model fitting and discrete spectra; The distributions of moving order statistics; Best invariant prediction region based on an adequate statistic; Estimation of the threshold parameter of the three parameter lognormal distributionA criterion for choosing the number of clusters in cluster analysis; On the development of SPMS as an effective tool for medical data analysis; Two approaches to nonparametric regression: splines & isotonic inference.
Inference and Prediction in Large Dimensions
| Author | : Denis Bosq |
| Publisher | : John Wiley & Sons |
| Total Pages | : 336 |
| Release | : 2008-03-11 |
| Genre | : Mathematics |
| ISBN | : 9780470724026 |
This book offers a predominantly theoretical coverage of statistical prediction, with some potential applications discussed, when data and/ or parameters belong to a large or infinite dimensional space. It develops the theory of statistical prediction, non-parametric estimation by adaptive projection – with applications to tests of fit and prediction, and theory of linear processes in function spaces with applications to prediction of continuous time processes. This work is in the Wiley-Dunod Series co-published between Dunod (www.dunod.com) and John Wiley and Sons, Ltd.
Nonparametric Predictive Inference
| Author | : Frank Coolen |
| Publisher | : Wiley-Blackwell |
| Total Pages | : 256 |
| Release | : 2012-06-15 |
| Genre | : |
| ISBN | : 9780470723340 |
This book will be the first on NPI and will provide an introduction to and overview of, the approach′s current state of the art. It will be a self-contained treatment of the subject, introducing it to readers, and leading them on to a more advanced and specialist understanding. The Author compares and contrasts NPI theory with classical statistical theory, pointing out the ways in which NPI can enhance current research in areas ranging from operations research to engineering and artificial intelligence. After the initial introductory chapter, the book provides a series of chapters outlining the use of NPI in specific settings, e.g. for real-valued random quantities or for multinomial data. This will be followed by chapters detailing further applications in statistics, providing examples such as NPI for statistical quality and process control, reliability and operations research, with a variety of examples such as maintenance and replacement problems, queuing situations and risk reliability inferences. The foundations and ideas behind NPI will be presented along with an examination and comparison of more traditional approaches of classical and Bayesian statistics, providing further insights into the advantages of NPI. Future directions and the accommodation of multivariate data will also be discussed.
Nonparametric Statistical Inference
| Author | : Jean Dickinson Gibbons |
| Publisher | : CRC Press |
| Total Pages | : 652 |
| Release | : 2010-07-26 |
| Genre | : Mathematics |
| ISBN | : 1439896127 |
Proven Material for a Course on the Introduction to the Theory and/or on the Applications of Classical Nonparametric Methods Since its first publication in 1971, Nonparametric Statistical Inference has been widely regarded as the source for learning about nonparametric statistics. The fifth edition carries on this tradition while thoroughly revising at least 50 percent of the material. New to the Fifth Edition Updated and revised contents based on recent journal articles in the literature A new section in the chapter on goodness-of-fit tests A new chapter that offers practical guidance on how to choose among the various nonparametric procedures covered Additional problems and examples Improved computer figures This classic, best-selling statistics book continues to cover the most commonly used nonparametric procedures. The authors carefully state the assumptions, develop the theory behind the procedures, and illustrate the techniques using realistic research examples from the social, behavioral, and life sciences. For most procedures, they present the tests of hypotheses, confidence interval estimation, sample size determination, power, and comparisons of other relevant procedures. The text also gives examples of computer applications based on Minitab, SAS, and StatXact and compares these examples with corresponding hand calculations. The appendix includes a collection of tables required for solving the data-oriented problems. Nonparametric Statistical Inference, Fifth Edition provides in-depth yet accessible coverage of the theory and methods of nonparametric statistical inference procedures. It takes a practical approach that draws on scores of examples and problems and minimizes the theorem-proof format. Jean Dickinson Gibbons was recently interviewed regarding her generous pledge to Virginia Tech.
