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Deconvolution Problems In Nonparametric Statistics
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Book Synopsis Deconvolution Problems in Nonparametric Statistics by : Alexander Meister
Download or read book Deconvolution Problems in Nonparametric Statistics written by Alexander Meister and published by Springer Science & Business Media. This book was released on 2009-12-24 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deconvolution problems occur in many ?elds of nonparametric statistics, for example, density estimation based on contaminated data, nonparametric - gression with errors-in-variables, image and signal deblurring. During the last two decades, those topics have received more and more attention. As appli- tions of deconvolution procedures concern many real-life problems in eco- metrics, biometrics, medical statistics, image reconstruction, one can realize an increasing number of applied statisticians who are interested in nonpa- metric deconvolution methods; on the other hand, some deep results from Fourier analysis, functional analysis, and probability theory are required to understand the construction of deconvolution techniques and their properties so that deconvolution is also particularly challenging for mathematicians. Thegeneraldeconvolutionprobleminstatisticscanbedescribedasfollows: Our goal is estimating a function f while any empirical access is restricted to some quantity h = f?G = f(x?y)dG(y), (1. 1) that is, the convolution of f and some probability distribution G. Therefore, f can be estimated from some observations only indirectly. The strategy is ˆ estimating h ?rst; this means producing an empirical version h of h and, then, ˆ applying a deconvolution procedure to h to estimate f. In the mathematical context, we have to invert the convolution operator with G where some reg- ˆ ularization is required to guarantee that h is contained in the invertibility ˆ domain of the convolution operator. The estimator h has to be chosen with respect to the speci?c statistical experiment.
Book Synopsis On the Optimal Rates of Convergence for Nonparametric Deconvolution Problem by : Jianqing Fan
Download or read book On the Optimal Rates of Convergence for Nonparametric Deconvolution Problem written by Jianqing Fan and published by . This book was released on 1988 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Optimal Global Rates of Convergence for Nonparametric Deconvolution Problem by : Jianqing Fan
Download or read book Optimal Global Rates of Convergence for Nonparametric Deconvolution Problem written by Jianqing Fan and published by . This book was released on 1988 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Concept of Energy in Nonparametric Statistics Goodness of Fit Problems and Deconvolution by : Berkan Aslan
Download or read book The Concept of Energy in Nonparametric Statistics Goodness of Fit Problems and Deconvolution written by Berkan Aslan and published by . This book was released on 2004 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Nonparametric Density Function Estimation and the Deconvolution Problem by : Ming-Chung Liu
Download or read book Nonparametric Density Function Estimation and the Deconvolution Problem written by Ming-Chung Liu and published by . This book was released on 1987 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Simple Kernel Estimators for Certain Nonparametric Deconvolution Problems by : Albertus Jacob Es
Download or read book Simple Kernel Estimators for Certain Nonparametric Deconvolution Problems written by Albertus Jacob Es and published by . This book was released on 1997 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Multi Bandwidth Kernel Estimators for Nonparametric Deconvolution Problems by : A. J. van Es
Download or read book Multi Bandwidth Kernel Estimators for Nonparametric Deconvolution Problems written by A. J. van Es and published by . This book was released on 1999 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Aspects of Nonparametric Density Estimation by : A. J. van Es
Download or read book Aspects of Nonparametric Density Estimation written by A. J. van Es and published by . This book was released on 1991 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Convex Minorant Estimators of Distributions in Nonparametric Deconvolution Problems by : Aren J. H. van Es (Physiologist, Netherlands)
Download or read book Convex Minorant Estimators of Distributions in Nonparametric Deconvolution Problems written by Aren J. H. van Es (Physiologist, Netherlands) and published by . This book was released on 1990 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis On the Effect of Estimating the Error Density in Nonparametric Deconvolution by : Michael H. Neumann
Download or read book On the Effect of Estimating the Error Density in Nonparametric Deconvolution written by Michael H. Neumann and published by . This book was released on 1995 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 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 Nonparametric Statistics for Stochastic Processes by : D. Bosq
Download or read book Nonparametric Statistics for Stochastic Processes written by D. Bosq and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is devoted to the theory and applications of nonparametic functional estimation and prediction. Chapter 1 provides an overview of inequalities and limit theorems for strong mixing processes. Density and regression estimation in discrete time are studied in Chapter 2 and 3. The special rates of convergence which appear in continuous time are presented in Chapters 4 and 5. This second edition is extensively revised and it contains two new chapters. Chapter 6 discusses the surprising local time density estimator. Chapter 7 gives a detailed account of implementation of nonparametric method and practical examples in economics, finance and physics. Comarison with ARMA and ARCH methods shows the efficiency of nonparametric forecasting. The prerequisite is a knowledge of classical probability theory and statistics. Denis Bosq is Professor of Statistics at the Unviersity of Paris 6 (Pierre et Marie Curie). He is Editor-in-Chief of "Statistical Inference for Stochastic Processes" and an editor of "Journal of Nonparametric Statistics". He is an elected member of the International Statistical Institute. He has published about 90 papers or works in nonparametric statistics and four books.
Book Synopsis Stochastic Models, Statistics and Their Applications by : Ansgar Steland
Download or read book Stochastic Models, Statistics and Their Applications written by Ansgar Steland and published by Springer. This book was released on 2015-02-04 with total page 479 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents the latest advances and trends in stochastic models and related statistical procedures. Selected peer-reviewed contributions focus on statistical inference, quality control, change-point analysis and detection, empirical processes, time series analysis, survival analysis and reliability, statistics for stochastic processes, big data in technology and the sciences, statistical genetics, experiment design, and stochastic models in engineering. Stochastic models and related statistical procedures play an important part in furthering our understanding of the challenging problems currently arising in areas of application such as the natural sciences, information technology, engineering, image analysis, genetics, energy and finance, to name but a few. This collection arises from the 12th Workshop on Stochastic Models, Statistics and Their Applications, Wroclaw, Poland.
Book Synopsis Lectures on Probability Theory and Statistics by : Roland Dobrushin
Download or read book Lectures on Probability Theory and Statistics written by Roland Dobrushin and published by Springer. This book was released on 2006-11-13 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 222 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.
Book Synopsis Studies in Theoretical and Applied Statistics by : Nicola Salvati
Download or read book Studies in Theoretical and Applied Statistics written by Nicola Salvati and published by Springer Nature. This book was released on 2023-02-14 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes a wide selection of papers presented at the 50th Scientific Meeting of the Italian Statistical Society (SIS2021), held virtually on 21-25 June 2021. It covers a wide variety of subjects ranging from methodological and theoretical contributions to applied works and case studies, giving an excellent overview of the interests of the Italian statisticians and their international collaborations. Intended for researchers interested in theoretical and empirical issues, this volume provides interesting starting points for further research.
