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Introduction To Nonparametric Detection With Applications
26 December 2010

Introduction To Nonparametric Detection With Applications

Introduction To Nonparametric Detection With Applications

1975 | 253 | ISBN: 0122821505 | DJVU | 1 Mb

Statisticians have long been interested in the development and application of nonparametric statistical tests. Although engineers have unknowingly implemented nonparametric detectors in the past, only recently have engineers become aware of the advantages of nonparametric tests, and hence have only recently become interested in the theoretical analysis and application of these detectors. Because of these two facts, almost the entire development and analysis of nonparametric detectors has taken place in the statistical literature. ...
Applied Nonparametric Statistics in Reliability
21 May 2013

Applied Nonparametric Statistics in Reliability
Applied Nonparametric Statistics in Reliability
English | ISBN: 0857291173 | 2011 | PDF | 244 pages | 4 MB

Nonparametric statistics has probably become the leading methodology for researchers performing data analysis. It is nevertheless true that, whereas these methods have already proved highly effective in other applied areas of knowledge such as biostatistics or social sciences, nonparametric analyses in reliability currently form an interesting area of study that has not yet been fully explored.
Asymptotic Efficiency of Nonparametric Tests
26 December 2010

Asymptotic Efficiency of Nonparametric Tests

Asymptotic Efficiency of Nonparametric Tests

1995 | 296 | ISBN: 0521470293 | DJVU | 2 Mb

Making a substantiated choice of the most efficient statistical test is one of the basic problems of statistics. Asymptotic efficiency is an indispensable technique for comparing and ordering statistical tests in large samples. It is especially useful in nonparametric statistics where it is usually necessary to rely on heuristic tests. This monograph presents a unified treatment of the analysis and calculation of the asymptotic efficiencies of nonparametric tests. Powerful new methods are developed to evaluate explicitly different kinds of efficiencies. Of particular interest is the description of domains of the Bahadur local optimality and related characterization problems based on recent research by the author. Other Russian results are also published here for the first time in English. Researchers, professionals, and students in statistics will find this book invaluable. ...
Nonparametric Function Estimation, Modeling, and Simulation
26 December 2010

Nonparametric Function Estimation, Modeling, and Simulation

Nonparametric Function Estimation, Modeling, and Simulation

1987 | 320 | ISBN: 0898712610 | DJVU | 2 Mb

Topics emphasized in this book include nonparametric density estimation as an exploratory device plus the deeper models to which the exploratory analysis points, multi-dimensional data analysis, and analysis of remote sensing data, cancer progression, chaos theory, epidemiological modeling, and parallel based algorithms. New methods discussed are quick nonparametric density estimation based techniques for resampling and simulation based estimation techniques not requiring closed form solutions. ...
Nonparametric Curve Estimation: Methods, Theory and Applications
17 March 2011

Nonparametric Curve Estimation: Methods, Theory and Applications

Nonparametric Curve Estimation: Methods, Theory and Applications

1999 | 425 | ISBN: 0387987401 | PDF | 3 Mb

Appropriate for a one-semester course, this self-contained book is an introduction to nonparametric curve estimation theory. It may be used for teaching graduate students in statistics (in this case an intermediate statistical inference, on the level of the book by G. Casella and R. Berger (1990) "Statistical Inference", Brooks/Cole, is the prerequisite) as well as for diverse classes with students from other sciences including engineering, business, social, medical, and biology. ...
Nonparametric Econometric Methods
17 June 2010

Nonparametric Econometric Methods
Qi Li, Jeffrey Scott Racine, "Nonparametric Econometric Methods
Emerald Group Publishing Limited | 2009 | ISBN: 184950623X | 549 pages | PDF | 6,2 MB

This Volume of "Advances in Econometrics" contains a selection of papers presented initially at the 7th Annual Advances in Econometrics Conference held on the LSU campus in Baton Rouge, Louisiana during November 14-16, 2008. The theme of the conference was 'Nonparametric Econometric Methods',
Advanced Robust and Nonparametric Methods in Efficiency Analysis: Methodology and Applications (Studies in Productivity and Efficiency)
12 November 2013

Advanced Robust and Nonparametric Methods in Efficiency Analysis: Methodology and Applications (Studies in Productivity and Efficiency)
Advanced Robust and Nonparametric Methods in Efficiency Analysis: Methodology and Applications (Studies in Productivity and Efficiency)
Published: 2007-03-27 | ISBN: 0387351558, 1441941975 | PDF | 248 pages | 5 MB

Providing a systematic and comprehensive treatment of recent developments in efficiency analysis, this readable book makes available an intuitive yet rigorous presentation of advanced nonparametric and robust methods. This flexible toolbox can be used in theories based on the neoclassical theory of production and its alternatives, including evolutionary theories. The methods are complemented by empirical analysis of three different economic fields: scientific research, mutual funds industry and the insurance sector.
Local Polynomial Modelling and Its Applications
30 September 2011

Local Polynomial Modelling and Its Applications

Local Polynomial Modelling and Its Applications

1997 | 360 | ISBN: 0412983214 | DJVU | 3 Mb

Data-analytic approaches to regression problems, arising from many scientific disciplines are described in this book. The aim of these nonparametric methods is to relax assumptions on the form of a regression function and to let data search for a suitable function that describes the data well. The use of these nonparametric functions with parametric techniques can yield very powerful data analysis tools. Local polynomial modeling and its applications provides an up-to-date picture on state-of-the-art nonparametric regression techniques. The emphasis of the book is on methodologies rather than on theory, with a particular focus on applications of nonparametric techniques to various statistical problems. High-dimensional data-analytic tools are presented, and the book includes a variety of examples. This will be a valuable reference for research and applied statisticians, and will serve as a textbook for graduate students and others interested in nonparametric regression. ...
Robust Nonparametric Statistical Methods, Second Edition
14 November 2013

Robust Nonparametric Statistical Methods, Second Edition
Robust Nonparametric Statistical Methods, Second Edition
English | ISBN: 1439809089 | 2011 | 553 pages | PDF | 5 Mb

Presenting an extensive set of tools and methods for data analysis, Robust Nonparametric Statistical Methods, Second Edition covers univariate tests and estimates with extensions to linear models, multivariate models, times series models, experimental designs, and mixed models. It follows the approach of the first edition by developing rank-based methods from the unifying theme of geometry. This edition, however, includes more models and methods and significantly extends the possible analyses based on ranks.
Even You Can Learn Statistics: A Guide for Everyone Who Has Ever Been Afraid of Statistics
8 March 2013

Even You Can Learn Statistics: A Guide for Everyone Who Has Ever Been Afraid of Statistics
David M. Levine, David F. Stephan, “Even You Can Learn Statistics: A Guide for Everyone Who Has Ever Been Afraid of Statistics”
2004-09-24 | ISBN: 0131467573 | 312 pages | PDF | 7,3 MB


Now, there's an easy-to-use guide that will help you use statistics in youreveryday work or study. Experienced educators David Levine and DavidStephan help you learn statistics using plain English and with a minimum ofmathematics, but with many examples and worked-out problems.You'll benefit from reading a plain language definition for each statisticalconcept that is followed by an interpretation section that explains theimportance of the concept and how you can apply the concept to solveproblems. You'll learn about the common misconceptions about statistics thatpeople make, allowing you to better use statistics in your own work.