Download or read book Accurate Nonparametric Inference written by Christopher Stroude Withers and published by . This book was released on 1980 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Exact Nonparametric Inference written by Nitin R. Patel and published by Chapman & Hall/CRC. This book was released on 2008-06-15 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Compstat written by Wolfgang Härdle and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: This COMPSTAT 2002 book contains the Keynote, Invited, and Full Contributed papers presented in Berlin, August 2002. A companion volume including Short Communications and Posters is published on CD. The COMPSTAT 2002 is the 15th conference in a serie of biannual conferences with the objective to present the latest developments in Computational Statistics and is taking place from August 24th to August 28th, 2002. Previous COMPSTATs were in Vienna (1974), Berlin (1976), Leiden (1978), Edinburgh (1980), Toulouse (1982), Pra~ue (1984), Rome (1986), Copenhagen (1988), Dubrovnik (1990), Neuchatel (1992), Vienna (1994), Barcelona (1996), Bris tol (1998) and Utrecht (2000). COMPSTAT 2002 is organised by CASE, Center of Applied Statistics and Eco nomics at Humboldt-Universitat zu Berlin in cooperation with F'reie Universitat Berlin and University of Potsdam. The topics of COMPSTAT include methodological applications, innovative soft ware and mathematical developments, especially in the following fields: statistical risk management, multivariate and robust analysis, Markov Chain Monte Carlo Methods, statistics of E-commerce, new strategies in teaching (Multimedia, In ternet), computerbased sampling/questionnaires, analysis of large databases (with emphasis on computing in memory), graphical tools for data analysis, classification and clustering, new statistical software and historical development of software.

Download or read book Nonparametric Statistical Inference written by Jean Dickinson Gibbons and published by CRC Press. This book was released on 2020-12-21 with total page 695 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Nonparametric Inference written by Z. Govindarajulu and published by World Scientific Publishing Company Incorporated. This book was released on 2007-01-01 with total page 669 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book StatXact written by and published by . This book was released on 1989 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Nonparametric Statistical Inference written by Jean Dickinson Gibbons and published by CRC Press. This book was released on 2014-03-10 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thoroughly revised and reorganized, the fourth edition presents in-depth coverage of the theory and methods of the most widely used nonparametric procedures in statistical analysis and offers example applications appropriate for all areas of the social, behavioral, and life sciences. The book presents new material on the quantiles, the calculation of exact and simulated power, multiple comparisons, additional goodness-of-fit tests, methods of analysis of count data, and modern computer applications using MINITAB, SAS, and STATXACT. It includes tabular guides for simplified applications of tests and finding P values and confidence interval estimates.

Download or read book Inference and Prediction in Large Dimensions written by Denis Bosq and published by John Wiley & Sons. This book was released on 2008-03-11 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Nonparametric Techniques in Statistical Inference written by Madan Lal Puri and published by Cambridge University Press. This book was released on 2009-01-08 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonparametric techniques in statistics are those in which the data are ranked in order according to some particular characteristic. When applied to measurable characteristics, the use of such techniques often saves considerable calculation as compared with more formal methods, with only slight loss of accuracy. The field of nonparametric statistics is occupying an increasingly important role in statistical theory as well as in its applications. Nonparametric methods are mathematically elegant, and they also yield significantly improved performances in applications to agriculture, education, biometrics, medicine, communication, economics and industry.

Download or read book Nonparametric Statistical Inference written by Jean Dickinson Gibbons and published by CRC Press. This book was released on 2010-07-26 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Parametric and Nonparametric Inference from Record Breaking Data written by Sneh Gulati and published by . This book was released on 2014-01-15 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Study of Nonparametric Inference Problems Using Monte Carlo Methods written by Hoi-Sheung Ho and published by . This book was released on 2017-01-26 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation, "A Study of Nonparametric Inference Problems Using Monte Carlo Methods" by Hoi-sheung, Ho, 何凱嫦, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Abstract of the thesis entitled A STUDY OF NONPARAMETRIC INFERENCE PROBLEMS USING MONTE CARLO METHODS submitted by Ho, Hoi Sheung for the degree of Doctor of Philosophy at The University of Hong Kong in December 2005 This study considered the problem of constructing condence intervals for non- standard interest parameters, such as the population quantile and the density function, based on random samples from univariate data distributions. The pri- mary objective is to generate improved condence intervals with higher coverage accuracy. In all the proposed methods, advanced Edgeworth expansions for ap- propriate distribution functions were established to derive the optimal coverage probabilitiesoftheintervals, andsimulationstudieswereconductedtoinvestigate the small-sample e(R)ects. The interval estimation problem was then extended to a regression setup, and the focus shifted to the more ambitious goal of carrying out nonparametric conditional inference for regression coecients. In the quantile case, rst an advanced bootstrap method which combines the itechniques of smoothing and iteration, was developed and shown to successfully improve the coverage accuracies of the bootstrap percentile and the bootstrap- t intervals for population quantiles. Second three di(R)erent methods of coverage calibration of simple linear interpolated intervals were proposed and shown to yield asymptotically more accurate coverage probabilities. In the density function case, a non-standard iterated bootstrap procedure whichrequiresbothunsmoothedandsmoothedouterbootstrapsamplesforboot- strapping kernel density estimates and relevant biases respectively, was proposed to reduce the coverage error of the bootstrap-t interval considerably. Finally, this study investigated the problem of constructing condence sets for regression coecients, conditional on an observed ancillary statistic, where the unknown error distribution is specied nonparametrically. The conditional asymptoticnormalityoftheregressioncoecientestimatorsunderregularitycon- ditions was established and the approach of plugging in kernel density estimators in conditional condence procedures was justied formally. ii DOI: 10.5353/th_b3577447 Subjects: Nonparametric statistics Monte Carlo method Confidence intervals

Download or read book Nonparametric Inference written by Zakkula Govindarajulu and published by World Scientific. This book was released on 2007-04-27 with total page 692 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Nonparametric Inference on Manifolds written by Abhishek Bhattacharya and published by Cambridge University Press. This book was released on 2012-04-05 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book StatXact 5 written by and published by . This book was released on 2002-02-01 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Nonparametric Predictive Inference for Ordinal Data and Accuracy of Diagnostic Tests written by Faiza F. Elkhafifi and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Exact Statistical Inference for Categorical Data written by Guogen Shan and published by Academic Press. This book was released on 2016-01-22 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exact Statistical Inference for Categorical Data discusses the way asymptotic approaches have been often used in practice to make statistical inference. This book introduces both conditional and unconditional exact approaches for the data in 2 by 2, or 2 by k contingency tables, and is an ideal reference for users who are interested in having the convenience of applying asymptotic approaches, with less computational time. In addition to the existing conditional exact inference, some efficient, unconditional exact approaches could be used in data analysis to improve the performance of the testing procedure. - Demonstrates how exact inference can be used to analyze data in 2 by 2 tables - Discusses the analysis of data in 2 by k tables using exact inference - Explains how exact inference can be used in genetics