Nonparametric Inference
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Nonparametric Inference
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Author : Z. Govindarajulu
language : en
Publisher: World Scientific
Release Date : 2007
Nonparametric Inference written by Z. Govindarajulu and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Mathematics categories.
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.
Nonparametric Inference Of Utilites
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Author : Matthias Herfert
language : en
Publisher: diplom.de
Release Date : 2006-12-06
Nonparametric Inference Of Utilites written by Matthias Herfert and has been published by diplom.de this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-12-06 with Business & Economics categories.
Inhaltsangabe:Abstract: In Chapter 2, Foundations , we provide a description of selected parts of theories which we believe are helpful to better understand the contribution of this thesis. We start with the presentation of several behavioral hypotheses in preference and utility theory. Next, we describe the basics of inferential statistics and Conjoint Analysis. Then, we describe probabilistic entropy, in addition to that a later established version of it, and its axiomatization as a general inference principle. We conclude Chapter 2 by presenting La Mura's decision-theoretic entropy, a version of entropy as an inference technique for expected utilities. La Mura had developed this connection between probabilistic entropy and expected utilities in his Ph.D. thesis. Based on his work, the initial research objective for this dissertation had been to make his approach applicable to the inference of unique consumer utilities given some observed evidence, having in mind the vast amounts of data that nowadays are available to analysts but still not used very effectively, in order to jointly overcome the limitations of Conjoint Analysis as mentioned above. In the following five chapters you will see that our research has instead resulted in a new method, namely Entropy Analysis, which is not based on expected utility functions but on ordinary utility functions. We close Chapter 2 with a conclusion for the following chapters. In Chapter 3, Entropy Analysis , we derive the new method combining probabilistic cross-entropy and ordinary utility functions. We start by imposing a set of conditions on the inference method. Then, we suggest a normalization of utility functions such that they become formally a probability measure. Finally, we present and prove our main result. In Chapter 4, Irrational Behavior , we present a solution for the problem of how to treat observed irrational behavior (see Definition 4.1) with Entropy Analysis. This is motivated by two reasons. First, we are hardly able to observe perfectly rational data in any survey or for any given set of transaction data. Therefore, any utility inference method that cannot deal with irrational data will not be meaningful for research or commercial applications. Second, our method is at first sight formally structured in a way in which its application to irrational data would return an inferred utility function that is trivial, i.e. uniform (to be further explained at the beginning of the [...]
Nonparametric Statistical Inference
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Author : Jean Dickinson Gibbons
language : en
Publisher: CRC Press
Release Date : 2010-07-26
Nonparametric Statistical Inference written by Jean Dickinson Gibbons and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-26 with Mathematics categories.
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.
Recent Developments In Nonparametric Inference And Probability
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Author :
language : en
Publisher: IMS
Release Date : 2006
Recent Developments In Nonparametric Inference And Probability written by and has been published by IMS this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Nonparametric statistics categories.
Parametric And Nonparametric Inference From Record Breaking Data
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Author : Sneh Gulati
language : en
Publisher: Springer Science & Business Media
Release Date : 2003-01-27
Parametric And Nonparametric Inference From Record Breaking Data written by Sneh Gulati and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-01-27 with Mathematics categories.
By providing a comprehensive look at statistical inference from record-breaking data in both parametric and nonparametric settings, this book treats the area of nonparametric function estimation from such data in detail. Its main purpose is to fill this void on general inference from record values. Statisticians, mathematicians, and engineers will find the book useful as a research reference. It can also serve as part of a graduate-level statistics or mathematics course.
Parametric And Nonparametric Inference For Statistical Dynamic Shape Analysis With Applications
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Author : Chiara Brombin
language : en
Publisher: Springer
Release Date : 2016-02-11
Parametric And Nonparametric Inference For Statistical Dynamic Shape Analysis With Applications written by Chiara Brombin and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-02-11 with Mathematics categories.
This book considers specific inferential issues arising from the analysis of dynamic shapes with the attempt to solve the problems at hand using probability models and nonparametric tests. The models are simple to understand and interpret and provide a useful tool to describe the global dynamics of the landmark configurations. However, because of the non-Euclidean nature of shape spaces, distributions in shape spaces are not straightforward to obtain. The book explores the use of the Gaussian distribution in the configuration space, with similarity transformations integrated out. Specifically, it works with the offset-normal shape distribution as a probability model for statistical inference on a sample of a temporal sequence of landmark configurations. This enables inference for Gaussian processes from configurations onto the shape space. The book is divided in two parts, with the first three chapters covering material on the offset-normal shape distribution, and the remaining chapters covering the theory of NonParametric Combination (NPC) tests. The chapters offer a collection of applications which are bound together by the theme of this book. They refer to the analysis of data from the FG-NET (Face and Gesture Recognition Research Network) database with facial expressions. For these data, it may be desirable to provide a description of the dynamics of the expressions, or testing whether there is a difference between the dynamics of two facial expressions or testing which of the landmarks are more informative in explaining the pattern of an expression.
Recent Developments In Nonparametric Inference And Probability
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Author : Jiayang Sun
language : en
Publisher:
Release Date : 2006
Recent Developments In Nonparametric Inference And Probability written by Jiayang Sun and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Nonparametric statistics categories.
All Of Nonparametric Statistics
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Author : Larry Wasserman
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-09-10
All Of Nonparametric Statistics written by Larry Wasserman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-09-10 with Mathematics categories.
There are many books on various aspects of nonparametric inference such as density estimation, nonparametric regression, bootstrapping, and wavelets methods. But it is hard to ?nd all these topics covered in one place. The goal of this text is to provide readers with a single book where they can ?nd a brief account of many of the modern topics in nonparametric inference. The book is aimed at master’s-level or Ph. D. -level statistics and computer science students. It is also suitable for researchersin statistics, machine lea- ing and data mining who want to get up to speed quickly on modern n- parametric methods. My goal is to quickly acquaint the reader with the basic concepts in many areas rather than tackling any one topic in great detail. In the interest of covering a wide range of topics, while keeping the book short, I have opted to omit most proofs. Bibliographic remarks point the reader to references that contain further details. Of course, I have had to choose topics to include andto omit,the title notwithstanding. For the mostpart,I decided to omit topics that are too big to cover in one chapter. For example, I do not cover classi?cation or nonparametric Bayesian inference. The book developed from my lecture notes for a half-semester (20 hours) course populated mainly by master’s-level students. For Ph. D.
Parametric And Nonparametric Inference From Record Breaking Data
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Author : Sneh Gulati
language : en
Publisher:
Release Date : 2014-01-15
Parametric And Nonparametric Inference From Record Breaking Data written by Sneh Gulati and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-15 with categories.
Perspectives In Mathematical Science I Probability And Statistics
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Author : N S Narasimha Sastry
language : en
Publisher: World Scientific
Release Date : 2009-07-06
Perspectives In Mathematical Science I Probability And Statistics written by N S Narasimha Sastry and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-07-06 with Mathematics categories.
This book presents a collection of invited articles by distinguished probabilists and statisticians on the occasion of the Platinum Jubilee Celebrations of the Indian Statistical Institute — a notable institute with significant achievement in research areas of statistics, probability and mathematics — in 2007.With a wide coverage of topics in probability and statistics, the articles provide a current perspective of different areas of research, emphasizing the major challenging issues. The book also proves its reference and utility value for practitioners as the articles in Statistics contain applications of the methodology that will be of use to practitioners. To professional statisticians and mathematicians, this is a unique volume for its illuminating perspectives on several important aspects of probability and statistics.