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Nonparametric Goodness Of Fit Testing Under Gaussian Models
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Book Synopsis Nonparametric Goodness-of-Fit Testing Under Gaussian Models by : Yuri Ingster
Download or read book Nonparametric Goodness-of-Fit Testing Under Gaussian Models written by Yuri Ingster and published by Springer Science & Business Media. This book was released on 2012-11-12 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the modern theory of nonparametric goodness-of-fit testing. It fills the gap in modern nonparametric statistical theory by discussing hypothesis testing and addresses mathematical statisticians who are interesting in the theory of non-parametric statistical inference. It will be of interest to specialists who are dealing with applied non-parametric statistical problems relevant in signal detection and transmission and in technical and medical diagnostics among others.
Book Synopsis Parametric and Nonparametric Inference from Record-Breaking Data by : Sneh Gulati
Download or read book Parametric and Nonparametric Inference from Record-Breaking Data written by Sneh Gulati and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Nonlinear Estimation and Classification by : David D. Denison
Download or read book Nonlinear Estimation and Classification written by David D. Denison and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: Researchers in many disciplines face the formidable task of analyzing massive amounts of high-dimensional and highly-structured data. This is due in part to recent advances in data collection and computing technologies. As a result, fundamental statistical research is being undertaken in a variety of different fields. Driven by the complexity of these new problems, and fueled by the explosion of available computer power, highly adaptive, non-linear procedures are now essential components of modern "data analysis," a term that we liberally interpret to include speech and pattern recognition, classification, data compression and signal processing. The development of new, flexible methods combines advances from many sources, including approximation theory, numerical analysis, machine learning, signal processing and statistics. The proposed workshop intends to bring together eminent experts from these fields in order to exchange ideas and forge directions for the future.
Book Synopsis Foundations of Statistical Inference by : Yoel Haitovsky
Download or read book Foundations of Statistical Inference written by Yoel Haitovsky and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a collection of papers presented at a conference held in Shoresh Holiday Resort near Jerusalem, Israel, in December 2000 organized by the Israeli Ministry of Science, Culture and Sport. The theme of the conference was "Foundation of Statistical Inference: Applications in the Medical and Social Sciences and in Industry and the Interface of Computer Sciences". The following is a quotation from the Program and Abstract booklet of the conference. "Over the past several decades, the field of statistics has seen tremendous growth and development in theory and methodology. At the same time, the advent of computers has facilitated the use of modern statistics in all branches of science, making statistics even more interdisciplinary than in the past; statistics, thus, has become strongly rooted in all empirical research in the medical, social, and engineering sciences. The abundance of computer programs and the variety of methods available to users brought to light the critical issues of choosing models and, given a data set, the methods most suitable for its analysis. Mathematical statisticians have devoted a great deal of effort to studying the appropriateness of models for various types of data, and defining the conditions under which a particular method work. " In 1985 an international conference with a similar title* was held in Is rael. It provided a platform for a formal debate between the two main schools of thought in Statistics, the Bayesian, and the Frequentists.
Book Synopsis Block Designs: A Randomization Approach by : Tadeusz Calinski
Download or read book Block Designs: A Randomization Approach written by Tadeusz Calinski and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is composed of two volumes, each consisting of five chapters. In Vol ume I, following some statistical motivation based on a randomization model, a general theory of the analysis of experiments in block designs has been de veloped. In the present Volume II, the primary aim is to present methods of that satisfy the statistical requirements described in constructing block designs Volume I, particularly those considered in Chapters 3 and 4, and also to give some catalogues of plans of the designs. Thus, the constructional aspects are of predominant interest in Volume II, with a general consideration given in Chapter 6. The main design investigations are systematized by separating the material into two contents, depending on whether the designs provide unit efficiency fac tors for some contrasts of treatment parameters (Chapter 7) or not (Chapter 8). This distinction in classifying block designs may be essential from a prac tical point of view. In general, classification of block designs, whether proper or not, is based here on efficiency balance (EB) in the sense of the new termi nology proposed in Section 4. 4 (see, in particular, Definition 4. 4. 2). Most of the attention is given to connected proper designs because of their statistical advantages as described in Volume I, particularly in Chapter 3. When all con trasts are of equal importance, either the class of (v - 1; 0; O)-EB designs, i. e.
Book Synopsis Missing and Modified Data in Nonparametric Estimation by : Sam Efromovich
Download or read book Missing and Modified Data in Nonparametric Estimation written by Sam Efromovich and published by CRC Press. This book was released on 2018-03-12 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a systematic and unified approach for modern nonparametric treatment of missing and modified data via examples of density and hazard rate estimation, nonparametric regression, filtering signals, and time series analysis. All basic types of missing at random and not at random, biasing, truncation, censoring, and measurement errors are discussed, and their treatment is explained. Ten chapters of the book cover basic cases of direct data, biased data, nondestructive and destructive missing, survival data modified by truncation and censoring, missing survival data, stationary and nonstationary time series and processes, and ill-posed modifications. The coverage is suitable for self-study or a one-semester course for graduate students with a prerequisite of a standard course in introductory probability. Exercises of various levels of difficulty will be helpful for the instructor and self-study. The book is primarily about practically important small samples. It explains when consistent estimation is possible, and why in some cases missing data should be ignored and why others must be considered. If missing or data modification makes consistent estimation impossible, then the author explains what type of action is needed to restore the lost information. The book contains more than a hundred figures with simulated data that explain virtually every setting, claim, and development. The companion R software package allows the reader to verify, reproduce and modify every simulation and used estimators. This makes the material fully transparent and allows one to study it interactively. Sam Efromovich is the Endowed Professor of Mathematical Sciences and the Head of the Actuarial Program at the University of Texas at Dallas. He is well known for his work on the theory and application of nonparametric curve estimation and is the author of Nonparametric Curve Estimation: Methods, Theory, and Applications. Professor Sam Efromovich is a Fellow of the Institute of Mathematical Statistics and the American Statistical Association.
Book Synopsis Statistical Models and Methods for Reliability and Survival Analysis by : Vincent Couallier
Download or read book Statistical Models and Methods for Reliability and Survival Analysis written by Vincent Couallier and published by John Wiley & Sons. This book was released on 2013-12-11 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Models and Methods for Reliability and Survival Analysis brings together contributions by specialists in statistical theory as they discuss their applications providing up-to-date developments in methods used in survival analysis, statistical goodness of fit, stochastic processes for system reliability, amongst others. Many of these are related to the work of Professor M. Nikulin in statistics over the past 30 years. The authors gather together various contributions with a broad array of techniques and results, divided into three parts - Statistical Models and Methods, Statistical Models and Methods in Survival Analysis, and Reliability and Maintenance. The book is intended for researchers interested in statistical methodology and models useful in survival analysis, system reliability and statistical testing for censored and non-censored data.
Book Synopsis Topics in Stochastic Analysis and Nonparametric Estimation by : Pao-Liu Chow
Download or read book Topics in Stochastic Analysis and Nonparametric Estimation written by Pao-Liu Chow and published by Springer Science & Business Media. This book was released on 2010-07-19 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: To honor Rafail Z. Khasminskii, on his seventy-fifth birthday, for his contributions to stochastic processes and nonparametric estimation theory an IMA participating institution conference entitled "Conference on Asymptotic Analysis in Stochastic Processes, Nonparametric Estimation, and Related Problems" was held. This volume commemorates this special event. Dedicated to Professor Khasminskii, it consists of nine papers on various topics in probability and statistics.
Book Synopsis Mathematical and Statistical Models and Methods in Reliability by : V.V. Rykov
Download or read book Mathematical and Statistical Models and Methods in Reliability written by V.V. Rykov and published by Springer Science & Business Media. This book was released on 2010-11-02 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is a selection of invited chapters, all of which deal with various aspects of mathematical and statistical models and methods in reliability. Written by renowned experts in the field of reliability, the contributions cover a wide range of applications, reflecting recent developments in areas such as survival analysis, aging, lifetime data analysis, artificial intelligence, medicine, carcinogenesis studies, nuclear power, financial modeling, aircraft engineering, quality control, and transportation. Mathematical and Statistical Models and Methods in Reliability is an excellent reference text for researchers and practitioners in applied probability and statistics, industrial statistics, engineering, medicine, finance, transportation, the oil and gas industry, and artificial intelligence.
Book Synopsis Testing Statistical Hypotheses by : E.L. Lehmann
Download or read book Testing Statistical Hypotheses written by E.L. Lehmann and published by Springer Nature. This book was released on 2022-06-22 with total page 1016 pages. Available in PDF, EPUB and Kindle. Book excerpt: The third edition of Testing Statistical Hypotheses updates and expands upon the classic graduate text, emphasizing optimality theory for hypothesis testing and confidence sets. The principal additions include a rigorous treatment of large sample optimality, together with the requisite tools. In addition, an introduction to the theory of resampling methods such as the bootstrap is developed. The sections on multiple testing and goodness of fit testing are expanded. The text is suitable for Ph.D. students in statistics and includes over 300 new problems out of a total of more than 760.
Book Synopsis Mathematical Foundations of Infinite-Dimensional Statistical Models by : Evarist Giné
Download or read book Mathematical Foundations of Infinite-Dimensional Statistical Models written by Evarist Giné and published by Cambridge University Press. This book was released on 2021-03-25 with total page 706 pages. Available in PDF, EPUB and Kindle. Book excerpt: In nonparametric and high-dimensional statistical models, the classical Gauss–Fisher–Le Cam theory of the optimality of maximum likelihood estimators and Bayesian posterior inference does not apply, and new foundations and ideas have been developed in the past several decades. This book gives a coherent account of the statistical theory in infinite-dimensional parameter spaces. The mathematical foundations include self-contained 'mini-courses' on the theory of Gaussian and empirical processes, approximation and wavelet theory, and the basic theory of function spaces. The theory of statistical inference in such models - hypothesis testing, estimation and confidence sets - is presented within the minimax paradigm of decision theory. This includes the basic theory of convolution kernel and projection estimation, but also Bayesian nonparametrics and nonparametric maximum likelihood estimation. In a final chapter the theory of adaptive inference in nonparametric models is developed, including Lepski's method, wavelet thresholding, and adaptive inference for self-similar functions. Winner of the 2017 PROSE Award for Mathematics.
Book Synopsis Nonparametric Monte Carlo Tests and Their Applications by : Li-Xing Zhu
Download or read book Nonparametric Monte Carlo Tests and Their Applications written by Li-Xing Zhu and published by Springer Science & Business Media. This book was released on 2005-08-09 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monte Carlo approximation to the null distribution of the test provides a convenient means of testing model fit. This book proposes a Monte Carlo-based methodology to construct this type of approximation when the model is semistructured. It addresses both applied and theoretical aspects of nonparametric Monte Carlo tests.
Author :Alexandre B. Tsybakov Publisher :Springer Science & Business Media ISBN 13 :0387790527 Total Pages :222 pages Book Rating :4.3/5 (877 download)
Book Synopsis Introduction to Nonparametric Estimation by : Alexandre B. Tsybakov
Download or read book Introduction to Nonparametric Estimation written by Alexandre B. Tsybakov and published by Springer Science & Business Media. This book was released on 2008-10-22 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Developed from lecture notes and ready to be used for a course on the graduate level, this concise text aims to introduce the fundamental concepts of nonparametric estimation theory while maintaining the exposition suitable for a first approach in the field.
Book Synopsis Topics in Statistical Simulation by : V.B. Melas
Download or read book Topics in Statistical Simulation written by V.B. Melas and published by Springer. This book was released on 2014-12-05 with total page 539 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Department of Statistical Sciences of the University of Bologna in collaboration with the Department of Management and Engineering of the University of Padova, the Department of Statistical Modelling of Saint Petersburg State University, and INFORMS Simulation Society sponsored the Seventh Workshop on Simulation. This international conference was devoted to statistical techniques in stochastic simulation, data collection, analysis of scientific experiments, and studies representing broad areas of interest. The previous workshops took place in St. Petersburg, Russia in 1994, 1996, 1998, 2001, 2005, and 2009. The Seventh Workshop took place in the Rimini Campus of the University of Bologna, which is in Rimini’s historical center.
Book Synopsis Foundations of Modern Statistics by : Denis Belomestny
Download or read book Foundations of Modern Statistics written by Denis Belomestny and published by Springer Nature. This book was released on 2023-07-16 with total page 603 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains contributions from the participants of the international conference “Foundations of Modern Statistics” which took place at Weierstrass Institute for Applied Analysis and Stochastics (WIAS), Berlin, during November 6–8, 2019, and at Higher School of Economics (HSE University), Moscow, during November 30, 2019. The events were organized in honor of Professor Vladimir Spokoiny on the occasion of his 60th birthday. Vladimir Spokoiny has pioneered the field of adaptive statistical inference and contributed to a variety of its applications. His more than 30 years of research in the field of mathematical statistics had a great influence on the development of the mathematical theory of statistics to its present state. It has inspired many young researchers to start their research in this exciting field of mathematics. The papers contained in this book reflect the broad field of interests of Vladimir Spokoiny: optimal rates and non-asymptotic bounds in nonparametrics, Bayes approaches from a frequentist point of view, optimization, signal processing, and statistical theory motivated by models in applied fields. Materials prepared by famous scientists contain original scientific results, which makes the publication valuable for researchers working in these fields. The book concludes by a conversation of Vladimir Spokoiny with Markus Reiβ and Enno Mammen. This interview gives some background on the life of Vladimir Spokoiny and his many scientific interests and motivations.
Book Synopsis Statistical Models and Methods for Biomedical and Technical Systems by : Filia Vonta
Download or read book Statistical Models and Methods for Biomedical and Technical Systems written by Filia Vonta and published by Springer Science & Business Media. This book was released on 2008-03-05 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with the mathematical aspects of survival analysis and reliability as well as other topics, reflecting recent developments in the following areas: applications in epidemiology; probabilistic and statistical models and methods in reliability; models and methods in survival analysis, longevity, aging, and degradation; accelerated life models; quality of life; new statistical challenges in genomics. The work will be useful to a broad interdisciplinary readership of researchers and practitioners in applied probability and statistics, industrial statistics, biomedicine, biostatistics, and engineering.
Book Synopsis Dependence in Probability and Statistics by : Paul Doukhan
Download or read book Dependence in Probability and Statistics written by Paul Doukhan and published by Springer Science & Business Media. This book was released on 2010-07-23 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: This account of recent works on weakly dependent, long memory and multifractal processes introduces new dependence measures for studying complex stochastic systems and includes other topics such as the dependence structure of max-stable processes.
