Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Missing And Modified Data In Nonparametric Estimation
Download Missing And Modified Data In Nonparametric Estimation full books in PDF, epub, and Kindle. Read online Missing And Modified Data In Nonparametric Estimation ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
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 951 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 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 Semiparametric Theory and Missing Data by : Anastasios Tsiatis
Download or read book Semiparametric Theory and Missing Data written by Anastasios Tsiatis and published by Springer Science & Business Media. This book was released on 2007-01-15 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Nonparametric Functional Estimation and Related Topics by : G.G Roussas
Download or read book Nonparametric Functional Estimation and Related Topics written by G.G Roussas and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 691 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Nonparametric Regression With the Scale Depending on Auxiliary Covariates and Missing Data by : Tian Jiang
Download or read book Nonparametric Regression With the Scale Depending on Auxiliary Covariates and Missing Data written by Tian Jiang and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Nonparametric Functional Estimation by : B. L. S. Prakasa Rao
Download or read book Nonparametric Functional Estimation written by B. L. S. Prakasa Rao and published by Academic Press. This book was released on 2014-07-10 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Advances in Longitudinal Survey Methodology by : Peter Lynn
Download or read book Advances in Longitudinal Survey Methodology written by Peter Lynn and published by John Wiley & Sons. This book was released on 2021-03-22 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Nonparametric Estimation of Cumulative Incidence Functions for Competing Risks Data with Missing Cause of Failure by : Georgios Effraimidis
Download or read book Nonparametric Estimation of Cumulative Incidence Functions for Competing Risks Data with Missing Cause of Failure written by Georgios Effraimidis and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Nonparametric Curve Estimation by : Sam Efromovich
Download or read book Nonparametric Curve Estimation written by Sam Efromovich and published by Springer Science & Business Media. This book was released on 2008-01-19 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Nonparametric Curve Estimation by : Sam Efromovich
Download or read book Nonparametric Curve Estimation written by Sam Efromovich and published by . This book was released on 2014-01-15 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Nonparametric Estimation of Probability Densities and Regression Curves by : Nadaraya
Download or read book Nonparametric Estimation of Probability Densities and Regression Curves written by Nadaraya and published by Springer. This book was released on 1988-12-31 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: ' this book is a useful and significant addition on the lively topic of nonparametric density and regression curve estimation.' Royal Statistical Society, 154, 1991
Book Synopsis Missing Data Methods by : David M. Drukker
Download or read book Missing Data Methods written by David M. Drukker and published by Emerald Group Publishing. This book was released on 2011-11-23 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contains 16 chapters authored by specialists in the field, covering topics such as: Missing-Data Imputation in Nonstationary Panel Data Models; Markov Switching Models in Empirical Finance; Bayesian Analysis of Multivariate Sample Selection Models Using Gaussian Copulas; and, Consistent Estimation and Orthogonality.
Book Synopsis Applied Nonparametric Statistics in Reliability by : M. Luz Gámiz
Download or read book Applied Nonparametric Statistics in Reliability written by M. Luz Gámiz and published by Springer Science & Business Media. This book was released on 2011-02-14 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 :Flow Regimes from International Experimental and Network Data (Project) Publisher : ISBN 13 :9781901502787 Total Pages :738 pages Book Rating :4.5/5 (27 download)
Book Synopsis Climate Variability and Change by : Flow Regimes from International Experimental and Network Data (Project)
Download or read book Climate Variability and Change written by Flow Regimes from International Experimental and Network Data (Project) and published by . This book was released on 2006 with total page 738 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Nonparametric Function Estimation, Modeling, and Simulation by : James R. Thompson
Download or read book Nonparametric Function Estimation, Modeling, and Simulation written by James R. Thompson and published by SIAM. This book was released on 1990-01-01 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: Topics emphasized in this book include nonparametric density estimation, multi-dimensional data analysis, cancer progression, chaos theory, and parallel based algorithms.
Book Synopsis All of Nonparametric Statistics by : Larry Wasserman
Download or read book All of Nonparametric Statistics written by Larry Wasserman and published by Springer Science & Business Media. This book was released on 2006-09-10 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text provides the reader with a single book where they can find accounts of a number of up-to-date issues in nonparametric inference. The book is aimed at Masters or PhD level students in statistics, computer science, and engineering. It is also suitable for researchers who want to get up to speed quickly on modern nonparametric methods. It covers a wide range of topics including the bootstrap, the nonparametric delta method, nonparametric regression, density estimation, orthogonal function methods, minimax estimation, nonparametric confidence sets, and wavelets. The book’s dual approach includes a mixture of methodology and theory.
Book Synopsis Nonparametric Statistics for Stochastic Processes by : Denis Bosq
Download or read book Nonparametric Statistics for Stochastic Processes written by Denis Bosq and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a mathematically rigorous treatment of the theory of nonparametric estimation and prediction for stochastic processes. It discusses discrete time and continuous time, and the emphasis is on the kernel methods. Several new results are presented concerning optimal and superoptimal convergence rates. How to implement the method is discussed in detail and several numerical results are presented. This book will be of interest to specialists in mathematical statistics and to those who wish to apply these methods to practical problems involving time series analysis.
