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Book Nonparametric Maximum Likelihood Estimators for Interval Censoring and Deconvolution

Download or read book Nonparametric Maximum Likelihood Estimators for Interval Censoring and Deconvolution written by Stanford University. Department of Statistics and published by . This book was released on 1991 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Nonparametric Maximum Likelihood Estimators for Interval Censoring and Deconvolution

Download or read book Nonparametric Maximum Likelihood Estimators for Interval Censoring and Deconvolution written by Petrus Groeneboom (wiskunde.) and published by . This book was released on 1991 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Information Bounds and Nonparametric Maximum Likelihood Estimation

Download or read book Information Bounds and Nonparametric Maximum Likelihood Estimation written by P. Groeneboom and published by Birkhäuser. This book was released on 2012-12-06 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the lecture notes for a DMV course presented by the authors at Gunzburg, Germany, in September, 1990. In the course we sketched the theory of information bounds for non parametric and semiparametric models, and developed the theory of non parametric maximum likelihood estimation in several particular inverse problems: interval censoring and deconvolution models. Part I, based on Jon Wellner's lectures, gives a brief sketch of information lower bound theory: Hajek's convolution theorem and extensions, useful minimax bounds for parametric problems due to Ibragimov and Has'minskii, and a recent result characterizing differentiable functionals due to van der Vaart (1991). The differentiability theorem is illustrated with the examples of interval censoring and deconvolution (which are pursued from the estimation perspective in part II). The differentiability theorem gives a way of clearly distinguishing situations in which 1 2 the parameter of interest can be estimated at rate n / and situations in which this is not the case. However it says nothing about which rates to expect when the functional is not differentiable. Even the casual reader will notice that several models are introduced, but not pursued in any detail; many problems remain. Part II, based on Piet Groeneboom's lectures, focuses on non parametric maximum likelihood estimates (NPMLE's) for certain inverse problems. The first chapter deals with the interval censoring problem.

Book Information Bounds and Nonparametric Maximum Likelihood Estimation

Download or read book Information Bounds and Nonparametric Maximum Likelihood Estimation written by P. Groeneboom and published by Birkhauser. This book was released on 1992 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Nonparametric Estimation under Shape Constraints

Download or read book Nonparametric Estimation under Shape Constraints written by Piet Groeneboom and published by Cambridge University Press. This book was released on 2014-12-11 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book treats the latest developments in the theory of order-restricted inference, with special attention to nonparametric methods and algorithmic aspects. Among the topics treated are current status and interval censoring models, competing risk models, and deconvolution. Methods of order restricted inference are used in computing maximum likelihood estimators and developing distribution theory for inverse problems of this type. The authors have been active in developing these tools and present the state of the art and the open problems in the field. The earlier chapters provide an introduction to the subject, while the later chapters are written with graduate students and researchers in mathematical statistics in mind. Each chapter ends with a set of exercises of varying difficulty. The theory is illustrated with the analysis of real-life data, which are mostly medical in nature.

Book Nonparametric Maximum Likelihood Estimation of the Cumulative Distribution Function with Multivariate Interval Censored Data

Download or read book Nonparametric Maximum Likelihood Estimation of the Cumulative Distribution Function with Multivariate Interval Censored Data written by Xuecheng Liu and published by . This book was released on 2002 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This thesis addresses nonparametric maximal likelihood (NPML) estimation of the cumulative distribution function (CDF) given multivariate interval censored data (MILD). The methodology consists in applying graph theory to the intersection graph of censored data. The maximal cliques of this graph and their real representations contain all the information needed to find NPML estimates (NPMLE). In this thesis, a new algorithm to determine the maximal cliques of an MICD set is introduced. The concepts of diameter and semi-diameter of the polytope formed by all NPMLEs are introduced and simulation to investigate the properties of the non-uniqueness polytope of the CDF NPMLEs for bivariate censored data is described. Also, an a priori bounding technique for the total mass attributed to a set of maximal cliques by a self-consistent estimate of the CDF (including the NPMLE) is presented." --

Book Nonparametric Maximum Likelihood Estimator Based on Doubly censored Data

Download or read book Nonparametric Maximum Likelihood Estimator Based on Doubly censored Data written by Ting Li and published by . This book was released on 1993 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Nonparametric Estimation under Shape Constraints

Download or read book Nonparametric Estimation under Shape Constraints written by Piet Groeneboom and published by Cambridge University Press. This book was released on 2014-12-11 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces basic concepts of shape constrained inference and guides the reader to current developments in the subject.

Book Analysis of Censored Data

Download or read book Analysis of Censored Data written by Hira L. Koul and published by IMS. This book was released on 1995 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Nonparametric Maximum Likelihood Estimation Based on Doubly censored Data

Download or read book Nonparametric Maximum Likelihood Estimation Based on Doubly censored Data written by Ding Li and published by . This book was released on 1993 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book On Nonparametric Estimation and Inference with Censored Data  Bandwidth Selection for Local Polynomial Regression  and Subset Selection in Explanatory Regression Analyses

Download or read book On Nonparametric Estimation and Inference with Censored Data Bandwidth Selection for Local Polynomial Regression and Subset Selection in Explanatory Regression Analyses written by Derick Randall Peterson and published by . This book was released on 1998 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Estimation in Interval Censorship Models

Download or read book Estimation in Interval Censorship Models written by Zhiming Wang and published by . This book was released on 1993 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Lectures on Probability Theory and Statistics

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 Unified Methods for Censored Longitudinal Data and Causality

Download or read book Unified Methods for Censored Longitudinal Data and Causality written by Mark J. van der Laan and published by Springer Science & Business Media. This book was released on 2012-11-12 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: A fundamental statistical framework for the analysis of complex longitudinal data is provided in this book. It provides the first comprehensive description of optimal estimation techniques based on time-dependent data structures. The techniques go beyond standard statistical approaches and can be used to teach masters and Ph.D. students. The text is ideally suitable for researchers in statistics with a strong interest in the analysis of complex longitudinal data.

Book Nonparametric Functional Estimation and Related Topics

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.