Non Standard Parametric Statistical Inference

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Non-Standard Parametric Statistical Inference

Author : Russell Cheng
Publisher : Oxford University Press
ISBN 13 : 0192518313
Total Pages : 432 pages
Book Rating : 4.1/5 (925 download)

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Book Synopsis Non-Standard Parametric Statistical Inference by : Russell Cheng

Download or read book Non-Standard Parametric Statistical Inference written by Russell Cheng and published by Oxford University Press. This book was released on 2017-09-15 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the fitting of parametric statistical models to data samples. Emphasis is placed on: (i) how to recognize situations where the problem is non-standard when parameter estimates behave unusually, and (ii) the use of parametric bootstrap resampling methods in analyzing such problems. A frequentist likelihood-based viewpoint is adopted, for which there is a well-established and very practical theory. The standard situation is where certain widely applicable regularity conditions hold. However, there are many apparently innocuous situations where standard theory breaks down, sometimes spectacularly. Most of the departures from regularity are described geometrically, with only sufficient mathematical detail to clarify the non-standard nature of a problem and to allow formulation of practical solutions. The book is intended for anyone with a basic knowledge of statistical methods, as is typically covered in a university statistical inference course, wishing to understand or study how standard methodology might fail. Easy to understand statistical methods are presented which overcome these difficulties, and demonstrated by detailed examples drawn from real applications. Simple and practical model-building is an underlying theme. Parametric bootstrap resampling is used throughout for analyzing the properties of fitted models, illustrating its ease of implementation even in non-standard situations. Distributional properties are obtained numerically for estimators or statistics not previously considered in the literature because their theoretical distributional properties are too hard to obtain theoretically. Bootstrap results are presented mainly graphically in the book, providing an accessible demonstration of the sampling behaviour of estimators.

Nonparametric Statistical Inference

Author : Jean Dickinson Gibbons
Publisher : CRC Press
ISBN 13 : 135161617X
Total Pages : 695 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis Nonparametric Statistical Inference by : Jean Dickinson Gibbons

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.

Notes on Non-parametric Statistical Inference

Author : Edwin J. G. Pitman
Publisher :
ISBN 13 :
Total Pages : 176 pages
Book Rating : 4.:/5 (1 download)

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Book Synopsis Notes on Non-parametric Statistical Inference by : Edwin J. G. Pitman

Download or read book Notes on Non-parametric Statistical Inference written by Edwin J. G. Pitman and published by . This book was released on 1949 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Nonparametric Statistical Inference

Author : Jean Dickinson Gibbons
Publisher : CRC Press
ISBN 13 : 1439896127
Total Pages : 652 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Nonparametric Statistical Inference by : Jean Dickinson Gibbons

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.

Nonparametric Statistical Inference

Author : Jean Dickinson Gibbons
Publisher : CRC Press
ISBN 13 : 113553201X
Total Pages : 350 pages
Book Rating : 4.1/5 (355 download)

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Book Synopsis Nonparametric Statistical Inference by : Jean Dickinson Gibbons

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.

Bootstrapping

Author : Christopher Z. Mooney
Publisher : SAGE
ISBN 13 : 9780803953819
Total Pages : 84 pages
Book Rating : 4.9/5 (538 download)

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Book Synopsis Bootstrapping by : Christopher Z. Mooney

Download or read book Bootstrapping written by Christopher Z. Mooney and published by SAGE. This book was released on 1993-08-09 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is. . . clear and well-written. . . anyone with any interest in the basis of quantitative analysis simply must read this book. . . . well-written, with a wealth of explanation. . ." --Dougal Hutchison in Educational Research Using real data examples, this volume shows how to apply bootstrapping when the underlying sampling distribution of a statistic cannot be assumed normal, as well as when the sampling distribution has no analytic solution. In addition, it discusses the advantages and limitations of four bootstrap confidence interval methods--normal approximation, percentile, bias-corrected percentile, and percentile-t. The book concludes with a convenient summary of how to apply this computer-intensive methodology using various available software packages.

Introduction to Non Parametric Methods through R Software

Author : Editor IJSMI
Publisher : International Journal of Statistics and Medical Informatics
ISBN 13 :
Total Pages : 78 pages
Book Rating : 4.3/5 (556 download)

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Book Synopsis Introduction to Non Parametric Methods through R Software by : Editor IJSMI

Download or read book Introduction to Non Parametric Methods through R Software written by Editor IJSMI and published by International Journal of Statistics and Medical Informatics. This book was released on 2022-09-30 with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Methods are widely used in Medical, Biological, Clinical, Business and Engineering field. The data which form the basis for the statistical methods helps us to take scientific and informed decisions. Statistical methods deal with the collection, compilation, analysis and making inference from the data. The book mainly focuses on non-parametric aspects of Statistical methods. Non parametric methods or tests are used when the assumption about the distribution of the variables in the data set is not known or does not follow normal distribution assumption. Non parametric methods are useful to deal with ordered categorical data. When the sample size is large, statistical tests are robust due to the central limit theorem property. When sample size is small one need to use non-parametric tests. Compared to parametric tests, non-parametric tests are less powerful i.e. if we fail to reject the null hypothesis even if it is false. When the data set involves ranks or measured in ordinal scale then non-parametric tests are useful and easy to construct than parametric tests. The book uses open source R statistical software to carry out different non-parametric statistical methods with sample datasets.

Long Range Dependence and Non-parametric Statistical Inference for Infinite-variance Random Functions

Author : Albert Rapp
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (143 download)

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Book Synopsis Long Range Dependence and Non-parametric Statistical Inference for Infinite-variance Random Functions by : Albert Rapp

Download or read book Long Range Dependence and Non-parametric Statistical Inference for Infinite-variance Random Functions written by Albert Rapp and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Nonparametric Inference

Author : Z. Govindarajulu
Publisher : World Scientific
ISBN 13 : 981270034X
Total Pages : 692 pages
Book Rating : 4.8/5 (127 download)

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Book Synopsis Nonparametric Inference by : Z. Govindarajulu

Download or read book Nonparametric Inference written by Z. Govindarajulu and published by World Scientific. This book was released on 2007 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.

PROBABILITY AND STATISTICS - Volume II

Author : Reinhard Viertl
Publisher : EOLSS Publications
ISBN 13 : 1848260539
Total Pages : 520 pages
Book Rating : 4.8/5 (482 download)

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Book Synopsis PROBABILITY AND STATISTICS - Volume II by : Reinhard Viertl

Download or read book PROBABILITY AND STATISTICS - Volume II written by Reinhard Viertl and published by EOLSS Publications. This book was released on 2009-06-11 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probability and Statistics theme is a component of Encyclopedia of Mathematical Sciences in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty one Encyclopedias. The Theme with contributions from distinguished experts in the field, discusses Probability and Statistics. Probability is a standard mathematical concept to describe stochastic uncertainty. Probability and Statistics can be considered as the two sides of a coin. They consist of methods for modeling uncertainty and measuring real phenomena. Today many important political, health, and economic decisions are based on statistics. This theme is structured in five main topics: Probability and Statistics; Probability Theory; Stochastic Processes and Random Fields; Probabilistic Models and Methods; Foundations of Statistics, which are then expanded into multiple subtopics, each as a chapter. These three volumes are aimed at the following five major target audiences: University and College students Educators, Professional practitioners, Research personnel and Policy analysts, managers, and decision makers and NGOs.

All of Statistics

Author : Larry Wasserman
Publisher : Springer Science & Business Media
ISBN 13 : 0387217363
Total Pages : 446 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis All of Statistics by : Larry Wasserman

Download or read book All of Statistics written by Larry Wasserman and published by Springer Science & Business Media. This book was released on 2013-12-11 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.

Mathematical Statistics

Author : Richard J. Rossi
Publisher : John Wiley & Sons
ISBN 13 : 1118771168
Total Pages : 611 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis Mathematical Statistics by : Richard J. Rossi

Download or read book Mathematical Statistics written by Richard J. Rossi and published by John Wiley & Sons. This book was released on 2018-06-14 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents a unified approach to parametric estimation, confidence intervals, hypothesis testing, and statistical modeling, which are uniquely based on the likelihood function This book addresses mathematical statistics for upper-undergraduates and first year graduate students, tying chapters on estimation, confidence intervals, hypothesis testing, and statistical models together to present a unifying focus on the likelihood function. It also emphasizes the important ideas in statistical modeling, such as sufficiency, exponential family distributions, and large sample properties. Mathematical Statistics: An Introduction to Likelihood Based Inference makes advanced topics accessible and understandable and covers many topics in more depth than typical mathematical statistics textbooks. It includes numerous examples, case studies, a large number of exercises ranging from drill and skill to extremely difficult problems, and many of the important theorems of mathematical statistics along with their proofs. In addition to the connected chapters mentioned above, Mathematical Statistics covers likelihood-based estimation, with emphasis on multidimensional parameter spaces and range dependent support. It also includes a chapter on confidence intervals, which contains examples of exact confidence intervals along with the standard large sample confidence intervals based on the MLE's and bootstrap confidence intervals. There’s also a chapter on parametric statistical models featuring sections on non-iid observations, linear regression, logistic regression, Poisson regression, and linear models. Prepares students with the tools needed to be successful in their future work in statistics data science Includes practical case studies including real-life data collected from Yellowstone National Park, the Donner party, and the Titanic voyage Emphasizes the important ideas to statistical modeling, such as sufficiency, exponential family distributions, and large sample properties Includes sections on Bayesian estimation and credible intervals Features examples, problems, and solutions Mathematical Statistics: An Introduction to Likelihood Based Inference is an ideal textbook for upper-undergraduate and graduate courses in probability, mathematical statistics, and/or statistical inference.

Statistical Inference in Financial and Insurance Mathematics with R

Author : Alexandre Brouste
Publisher : Elsevier
ISBN 13 : 0081012616
Total Pages : 204 pages
Book Rating : 4.0/5 (81 download)

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Book Synopsis Statistical Inference in Financial and Insurance Mathematics with R by : Alexandre Brouste

Download or read book Statistical Inference in Financial and Insurance Mathematics with R written by Alexandre Brouste and published by Elsevier. This book was released on 2017-11-22 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finance and insurance companies are facing a wide range of parametric statistical problems. Statistical experiments generated by a sample of independent and identically distributed random variables are frequent and well understood, especially those consisting of probability measures of an exponential type. However, the aforementioned applications also offer non-classical experiments implying observation samples of independent but not identically distributed random variables or even dependent random variables. Three examples of such experiments are treated in this book. First, the Generalized Linear Models are studied. They extend the standard regression model to non-Gaussian distributions. Statistical experiments with Markov chains are considered next. Finally, various statistical experiments generated by fractional Gaussian noise are also described. In this book, asymptotic properties of several sequences of estimators are detailed. The notion of asymptotical efficiency is discussed for the different statistical experiments considered in order to give the proper sense of estimation risk. Eighty examples and computations with R software are given throughout the text. Examines a range of statistical inference methods in the context of finance and insurance applications Presents the LAN (local asymptotic normality) property of likelihoods Combines the proofs of LAN property for different statistical experiments that appears in financial and insurance mathematics Provides the proper description of such statistical experiments and invites readers to seek optimal estimators (performed in R) for such statistical experiments

Statistical Inference

Author : Paul H. Garthwaite
Publisher : OUP Oxford
ISBN 13 : 9780198572268
Total Pages : 346 pages
Book Rating : 4.5/5 (722 download)

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Book Synopsis Statistical Inference by : Paul H. Garthwaite

Download or read book Statistical Inference written by Paul H. Garthwaite and published by OUP Oxford. This book was released on 2002 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical inference is the foundation on which much of statistical practice is built. The book covers the topic at a level suitable for students and professionals who need to understand these foundations.

All of Nonparametric Statistics

Author : Larry Wasserman
Publisher : Springer Science & Business Media
ISBN 13 : 0387306234
Total Pages : 272 pages
Book Rating : 4.3/5 (873 download)

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Book Synopsis All of Nonparametric Statistics by : Larry Wasserman

Download or read book All of Nonparametric Statistics written by Larry Wasserman and published by Springer Science & Business Media. This book was released on 2006-09-10 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text provides the reader with a single book where they can find accounts of a number of up-to-date issues in nonparametric inference. The book is aimed at Masters or PhD level students in statistics, computer science, and engineering. It is also suitable for researchers who want to get up to speed quickly on modern nonparametric methods. 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. The book’s dual approach includes a mixture of methodology and theory.

Parametric Statistical Inference

Author : Shelemyahu Zacks
Publisher : Elsevier
ISBN 13 : 1483150496
Total Pages : 404 pages
Book Rating : 4.4/5 (831 download)

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Book Synopsis Parametric Statistical Inference by : Shelemyahu Zacks

Download or read book Parametric Statistical Inference written by Shelemyahu Zacks and published by Elsevier. This book was released on 2014-05-20 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: Parametric Statistical Inference: Basic Theory and Modern Approaches presents the developments and modern trends in statistical inference to students who do not have advanced mathematical and statistical preparation. The topics discussed in the book are basic and common to many fields of statistical inference and thus serve as a jumping board for in-depth study. The book is organized into eight chapters. Chapter 1 provides an overview of how the theory of statistical inference is presented in subsequent chapters. Chapter 2 briefly discusses statistical distributions and their properties. Chapter 3 is devoted to the problem of sufficient statistics and the information in samples, and Chapter 4 presents some basic results from the theory of testing statistical hypothesis. In Chapter 5, the classical theory of estimation is developed. Chapter 6 discusses the efficiency of estimators and some large sample properties, while Chapter 7 studies the topics on confidence intervals. Finally, Chapter 8 is about decision theoretic and Bayesian approach in testing and estimation. Senior undergraduate and graduate students in statistics and mathematics, and those who have taken an introductory course in probability will highly benefit from this book.

Concepts of Nonparametric Theory

Author : J.W. Pratt
Publisher : Springer Science & Business Media
ISBN 13 : 1461259312
Total Pages : 476 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Concepts of Nonparametric Theory by : J.W. Pratt

Download or read book Concepts of Nonparametric Theory written by J.W. Pratt and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores both non parametric and general statistical ideas by developing non parametric procedures in simple situations. The major goal is to give the reader a thorough intuitive understanding of the concepts underlying nonparametric procedures and a full appreciation of the properties and operating characteristics of those procedures covered. This book differs from most statistics books by including considerable philosophical and methodological discussion. Special attention is given to discussion of the strengths and weaknesses of various statistical methods and approaches. Difficulties that often arise in applying statistical theory to real data also receive substantial attention. The approach throughout is more conceptual than mathematical. The "Theorem-Proof" format is avoided; generally, properties are "shown," rather than "proved." In most cases the ideas behind the proof of an im portant result are discussed intuitively in the text and formal details are left as an exercise for the reader. We feel that the reader will learn more from working such things out than from checking step-by-step a complete presen tation of all details.