Missing And Modified Data In Nonparametric Estimation

Author : Sam Efromovich
Publisher : CRC Press
Page : 951 pages
File Size : 51,6 Mb
Release : 2018-03-12
Category : Mathematics
ISBN : 9781351679831

Get Book

Missing and Modified Data in Nonparametric Estimation by Sam Efromovich Pdf

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.

Author : Sam Efromovich
Publisher : CRC Press
Page : 448 pages
File Size : 50,6 Mb
Release : 2018-03-12
Category : Mathematics
ISBN : 9781351679848

Get Book

Missing and Modified Data in Nonparametric Estimation by Sam Efromovich Pdf

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.

Author : G.G Roussas
Publisher : Springer Science & Business Media
Page : 691 pages
File Size : 44,6 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9789401132220

Get Book

Nonparametric Functional Estimation and Related Topics by G.G Roussas Pdf

About three years ago, an idea was discussed among some colleagues in the Division of Statistics at the University of California, Davis, as to the possibility of holding an international conference, focusing exclusively on nonparametric curve estimation. The fruition of this idea came about with the enthusiastic support of this project by Luc Devroye of McGill University, Canada, and Peter Robinson of the London School of Economics, UK. The response of colleagues, contacted to ascertain interest in participation in such a conference, was gratifying and made the effort involved worthwhile. Devroye and Robinson, together with this editor and George Metakides of the University of Patras, Greece and of the European Economic Communities, Brussels, formed the International Organizing Committee for a two week long Advanced Study Institute (ASI) sponsored by the Scientific Affairs Division of the North Atlantic Treaty Organization (NATO). The ASI was held on the Greek Island of Spetses between July 29 and August 10, 1990. Nonparametric functional estimation is a central topic in statistics, with applications in numerous substantive fields in mathematics, natural and social sciences, engineering and medicine. While there has been interest in nonparametric functional estimation for many years, this has grown of late, owing to increasing availability of large data sets and the ability to process them by means of improved computing facilities, along with the ability to display the results by means of sophisticated graphical procedures.

Author : Anastasios Tsiatis
Publisher : Springer Science & Business Media
Page : 392 pages
File Size : 46,9 Mb
Release : 2007-01-15
Category : Mathematics
ISBN : 9780387373454

Get Book

Semiparametric Theory and Missing Data by Anastasios Tsiatis Pdf

This book summarizes current knowledge regarding the theory of estimation for semiparametric models with missing data, in an organized and comprehensive manner. It starts with the study of semiparametric methods when there are no missing data. The description of the theory of estimation for semiparametric models is both rigorous and intuitive, relying on geometric ideas to reinforce the intuition and understanding of the theory. These methods are then applied to problems with missing, censored, and coarsened data with the goal of deriving estimators that are as robust and efficient as possible.

Author : B. L. S. Prakasa Rao
Publisher : Academic Press
Page : 538 pages
File Size : 51,7 Mb
Release : 2014-07-10
Category : Mathematics
ISBN : 9781483269238

Get Book

Nonparametric Functional Estimation by B. L. S. Prakasa Rao Pdf

Nonparametric Functional Estimation is a compendium of papers, written by experts, in the area of nonparametric functional estimation. This book attempts to be exhaustive in nature and is written both for specialists in the area as well as for students of statistics taking courses at the postgraduate level. The main emphasis throughout the book is on the discussion of several methods of estimation and on the study of their large sample properties. Chapters are devoted to topics on estimation of density and related functions, the application of density estimation to classification problems, and the different facets of estimation of distribution functions. Statisticians and students of statistics and engineering will find the text very useful.

Author : Tian Jiang
Publisher : Unknown
Page : 0 pages
File Size : 47,7 Mb
Release : 2022
Category : Heteroscedasticity
ISBN : OCLC:1417360108

Get Book

Nonparametric Regression With the Scale Depending on Auxiliary Covariates and Missing Data by Tian Jiang Pdf

Nonparametric curve estimation is a powerful statistical methodology which allows estimation of curves with no assumption about their shape. It provides useful insight into the nature of data and may guide further inference for specific parametric models. Considered statistical problem is a nonparametric heteroscedastic regression with auxiliary covariates and missing data. In this regression a univariate component is of the primary interest while the scale function is allowed to be dependent on both the predictor and auxiliary covariates. Missing mechanism is the missing at random (MAR), and two settings with missing responses or missing predictors are considered. The assumed MAR means that the probability of missing may depend on observed variables but not on missing variables. Developed asymptotic theory shows how the heteroscedasticity and MAR mechanism affect the constant of minimax convergence under the mean integrated squared error criterion. Further, it is shown that a procedure ignoring the scale function is not efficient and does not attain a sharp constant in the minimax lower bound. Models of missing responses and predictors are considered separately because their theory and methodology are different. For the case of missing responses, a sharp minimax and data-driven procedure is developed which is based on estimation of an unknown nuisance scale function. The estimator adapts to the MAR response mechanism and unknown smoothness of an underlying regression function. Further, efficiency is still preserved for a more general additive model with auxiliary covariates. A model with MAR predictors is dramatically more involved, and here classic regression estimators are no longer even consistent. For a model with MAR predictors a novel data-driven estimator is suggested which takes into account a scale function. This estimator is adaptive and matches performance of an oracle that knows all underlying nuisance functions. The asymptotic theory is extended to the case of a general additive model as well. The theory and methodology are tested using Monte Carlo simulation studies and real examples. The results favor the proposed methodology and support practical feasibility of the proposed methods for heteroscedastic regressions with missing data.

Author : Justin Wishart
Publisher : Unknown
Page : 442 pages
File Size : 44,8 Mb
Release : 2011
Category : Nonparametric statistics
ISBN : OCLC:796923456

Get Book

Nonparametric Estimation of Change-points in Derivatives by Justin Wishart Pdf

Author : Sam Efromovich
Publisher : Unknown
Page : 432 pages
File Size : 54,5 Mb
Release : 2014-01-15
Category : Electronic
ISBN : 1475773005

Get Book

Nonparametric Curve Estimation by Sam Efromovich Pdf

Author : Arthur Askew,Flow Regimes from International Experimental and Network Data (Project)
Publisher : Unknown
Page : 738 pages
File Size : 41,7 Mb
Release : 2006
Category : Cambio climático
ISBN : 1901502783

Get Book

Climate Variability and Change--hydrological Impacts by Arthur Askew,Flow Regimes from International Experimental and Network Data (Project) Pdf

This volume contains 117 reviewed papers from over 30 countries, published in English, French and Spanish, which reflect both international dimension of FRIEND and the key challenges facing hydrologists in the 21st century.

Author : Peter Lynn
Publisher : John Wiley & Sons
Page : 548 pages
File Size : 41,7 Mb
Release : 2021-03-22
Category : Mathematics
ISBN : 9781119376934

Get Book

Advances in Longitudinal Survey Methodology by Peter Lynn Pdf

Advances in Longitudinal Survey Methodology Explore an up-to-date overview of best practices in the implementation of longitudinal surveys from leading experts in the field of survey methodology Advances in Longitudinal Survey Methodology delivers a thorough review of the most current knowledge in the implementation of longitudinal surveys. The book provides a comprehensive overview of the many advances that have been made in the field of longitudinal survey methodology over the past fifteen years, as well as extending the topic coverage of the earlier volume, “Methodology of Longitudinal Surveys”, published in 2009. This new edited volume covers subjects like dependent interviewing, interviewer effects, panel conditioning, rotation group bias, measurement of cognition, and weighting. New chapters discussing the recent shift to mixed-mode data collection and obtaining respondents’ consent to data linkage add to the book’s relevance to students and social scientists seeking to understand modern challenges facing data collectors today. Readers will also benefit from the inclusion of: A thorough introduction to refreshment sampling for longitudinal surveys, including consideration of principles, sampling frame, sample design, questionnaire design, and frequency An exploration of the collection of biomarker data in longitudinal surveys, including detailed measurements of ill health, biological pathways, and genetics in longitudinal studies An examination of innovations in participant engagement and tracking in longitudinal surveys, including current practices and new evidence on internet and social media for participant engagement. An invaluable source for post-graduate students, professors, and researchers in the field of survey methodology, Advances in Longitudinal Survey Methodology will also earn a place in the libraries of anyone who regularly works with or conducts longitudinal surveys and requires a one-stop reference for the latest developments and findings in the field.

Author : M. Luz Gámiz,K. B. Kulasekera,Nikolaos Limnios,Bo Henry Lindqvist
Publisher : Springer Science & Business Media
Page : 230 pages
File Size : 45,8 Mb
Release : 2011-02-14
Category : Technology & Engineering
ISBN : 9780857291189

Get Book

Applied Nonparametric Statistics in Reliability by M. Luz Gámiz,K. B. Kulasekera,Nikolaos Limnios,Bo Henry Lindqvist Pdf

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. Applied Nonparametric Statistics in Reliability is focused on the use of modern statistical methods for the estimation of dependability measures of reliability systems that operate under different conditions. The scope of the book includes: smooth estimation of the reliability function and hazard rate of non-repairable systems; study of stochastic processes for modelling the time evolution of systems when imperfect repairs are performed; nonparametric analysis of discrete and continuous time semi-Markov processes; isotonic regression analysis of the structure function of a reliability system, and lifetime regression analysis. Besides the explanation of the mathematical background, several numerical computations or simulations are presented as illustrative examples. The corresponding computer-based methods have been implemented using R and MATLAB®. A concrete modelling scheme is chosen for each practical situation and, in consequence, a nonparametric inference procedure is conducted. Applied Nonparametric Statistics in Reliability will serve the practical needs of scientists (statisticians and engineers) working on applied reliability subjects.

Author : James R. Thompson,Richard A. Tapia
Publisher : SIAM
Page : 317 pages
File Size : 44,7 Mb
Release : 1990-01-01
Category : Mathematics
ISBN : 9780898712612

Get Book

Nonparametric Function Estimation, Modeling, and Simulation by James R. Thompson,Richard A. Tapia Pdf

Topics emphasized in this book include nonparametric density estimation, multi-dimensional data analysis, cancer progression, chaos theory, and parallel based algorithms.

Author : Nadaraya
Publisher : Springer
Page : 228 pages
File Size : 54,6 Mb
Release : 1988-12-31
Category : Mathematics
ISBN : 9027727570

Get Book

Nonparametric Estimation of Probability Densities and Regression Curves by Nadaraya Pdf

' this book is a useful and significant addition on the lively topic of nonparametric density and regression curve estimation.' Royal Statistical Society, 154, 1991

Author : Sam Efromovich
Publisher : Springer Science & Business Media
Page : 414 pages
File Size : 46,9 Mb
Release : 2008-01-19
Category : Mathematics
ISBN : 9780387226385

Get Book

Nonparametric Curve Estimation by Sam Efromovich Pdf

This book gives a systematic, comprehensive, and unified account of modern nonparametric statistics of density estimation, nonparametric regression, filtering signals, and time series analysis. The companion software package, available over the Internet, brings all of the discussed topics into the realm of interactive research. Virtually every claim and development mentioned in the book is illustrated with graphs which are available for the reader to reproduce and modify, making the material fully transparent and allowing for complete interactivity.

Author : Sam Efromovich
Publisher : Springer
Page : 414 pages
File Size : 43,6 Mb
Release : 2013-03-23
Category : Mathematics
ISBN : 1475773013

Get Book

Nonparametric Curve Estimation by Sam Efromovich Pdf

This book gives a systematic, comprehensive, and unified account of modern nonparametric statistics of density estimation, nonparametric regression, filtering signals, and time series analysis. The companion software package, available over the Internet, brings all of the discussed topics into the realm of interactive research. Virtually every claim and development mentioned in the book is illustrated with graphs which are available for the reader to reproduce and modify, making the material fully transparent and allowing for complete interactivity.