Robust Estimation in Measurement Error Models

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ISBN 13 :
Total Pages : 284 pages
Book Rating : 4.:/5 (27 download)

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Book Synopsis Robust Estimation in Measurement Error Models by : Joseph H. R. Croos

Download or read book Robust Estimation in Measurement Error Models written by Joseph H. R. Croos and published by . This book was released on 1992 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Robust Estimation Via Measurement Error Modeling

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ISBN 13 :
Total Pages : 91 pages
Book Rating : 4.:/5 (623 download)

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Book Synopsis Robust Estimation Via Measurement Error Modeling by : Qiong Wang

Download or read book Robust Estimation Via Measurement Error Modeling written by Qiong Wang and published by . This book was released on 2005 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: Keywords: measurement error model, robust estimation, MCMC, Bayesian, influence function.

Robust Estimation via Measurement Error Modeling

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ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (656 download)

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Book Synopsis Robust Estimation via Measurement Error Modeling by :

Download or read book Robust Estimation via Measurement Error Modeling written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We introduce a new method to robustifying inference that can be applied in any situation where a parametric likelihood is available. The key feature is that data from the postulated parametric models are assumed to be measured with error where the measurement error distribution is chosen to produce the occasional gross errors found in data. We show that the tails of the error-contamination model control the properties (boundedness, redescendingness) of the resulting influence functions, with heavier tails in the error contamination model producing more robust estimators. In the application to location-scale models with independent and identically distributed data, the resulting analytically-intractable likelihoods are approximated via Monte Carlo integration. In the application to time series models, we propose a Bayesian approach to the robust estimation of time series parameters. We use Markov Chain Monte Carlo (MCMC) to estimate the parameters of interest and also the gross errors. The latter are used as outlier diagnostics.

Robust Statistical Methods with R, Second Edition

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Publisher : CRC Press
ISBN 13 : 1351975137
Total Pages : 254 pages
Book Rating : 4.3/5 (519 download)

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Book Synopsis Robust Statistical Methods with R, Second Edition by : Jana Jurečková

Download or read book Robust Statistical Methods with R, Second Edition written by Jana Jurečková and published by CRC Press. This book was released on 2019-05-29 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of Robust Statistical Methods with R provides a systematic treatment of robust procedures with an emphasis on new developments and on the computational aspects. There are many numerical examples and notes on the R environment, and the updated chapter on the multivariate model contains additional material on visualization of multivariate data in R. A new chapter on robust procedures in measurement error models concentrates mainly on the rank procedures, less sensitive to errors than other procedures. This book will be an invaluable resource for researchers and postgraduate students in statistics and mathematics. Features • Provides a systematic, practical treatment of robust statistical methods • Offers a rigorous treatment of the whole range of robust methods, including the sequential versions of estimators, their moment convergence, and compares their asymptotic and finite-sample behavior • The extended account of multivariate models includes the admissibility, shrinkage effects and unbiasedness of two-sample tests • Illustrates the small sensitivity of the rank procedures in the measurement error model • Emphasizes the computational aspects, supplies many examples and illustrations, and provides the own procedures of the authors in the R software on the book’s website

Measurement Error

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Publisher : CRC Press
ISBN 13 : 1420066587
Total Pages : 465 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Measurement Error by : John P. Buonaccorsi

Download or read book Measurement Error written by John P. Buonaccorsi and published by CRC Press. This book was released on 2010-03-02 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last 20 years, comprehensive strategies for treating measurement error in complex models and accounting for the use of extra data to estimate measurement error parameters have emerged. Focusing on both established and novel approaches, Measurement Error: Models, Methods, and Applications provides an overview of the main techniques and illu

Statistical Analysis of Measurement Error Models and Applications

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Publisher : American Mathematical Soc.
ISBN 13 : 0821851179
Total Pages : 262 pages
Book Rating : 4.8/5 (218 download)

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Book Synopsis Statistical Analysis of Measurement Error Models and Applications by : Philip J. Brown

Download or read book Statistical Analysis of Measurement Error Models and Applications written by Philip J. Brown and published by American Mathematical Soc.. This book was released on 1990 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Measurement error models describe functional relationships among variables observed, subject to random errors of measurement. This book treats general aspects of the measurement problem and features a discussion of the history of measurement error models.

Introduction to Robust Estimation and Hypothesis Testing

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Publisher : Academic Press
ISBN 13 : 0123869838
Total Pages : 713 pages
Book Rating : 4.1/5 (238 download)

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Book Synopsis Introduction to Robust Estimation and Hypothesis Testing by : Rand R. Wilcox

Download or read book Introduction to Robust Estimation and Hypothesis Testing written by Rand R. Wilcox and published by Academic Press. This book was released on 2012-01-12 with total page 713 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book focuses on the practical aspects of modern and robust statistical methods. The increased accuracy and power of modern methods, versus conventional approaches to the analysis of variance (ANOVA) and regression, is remarkable. Through a combination of theoretical developments, improved and more flexible statistical methods, and the power of the computer, it is now possible to address problems with standard methods that seemed insurmountable only a few years ago"--

Measurement Error in Nonlinear Models

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Publisher : CRC Press
ISBN 13 : 9780412047213
Total Pages : 334 pages
Book Rating : 4.0/5 (472 download)

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Book Synopsis Measurement Error in Nonlinear Models by : Raymond J. Carroll

Download or read book Measurement Error in Nonlinear Models written by Raymond J. Carroll and published by CRC Press. This book was released on 1995-07-06 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph provides an up-to-date discussion of analysis strategies for regression problems in which predictor variables are measured with errors. The analysis of nonlinear regression models includes generalized linear models, transform-both-sides models and quasilikelihood and variance function problems. The text concentrates on the general ideas and strategies of estimation and inference rather than being concerned with a specific problem. Measurement error occurs in many fields, such as biometry, epidemiology and economics. In particular, the book contains a large number of epidemiological examples. An outline of strategies for handling progressively more difficult problems is also provided.

Robust Estimation and Testing

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Publisher : John Wiley & Sons
ISBN 13 : 1118165497
Total Pages : 382 pages
Book Rating : 4.1/5 (181 download)

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Book Synopsis Robust Estimation and Testing by : Robert G. Staudte

Download or read book Robust Estimation and Testing written by Robert G. Staudte and published by John Wiley & Sons. This book was released on 2011-09-15 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the theory and methods of robust statistics, providing students with practical methods for carrying out robust procedures in a variety of statistical contexts and explaining the advantages of these procedures. In addition, the text develops techniques and concepts likely to be useful in the future analysis of new statistical models and procedures. Emphasizing the concepts of breakdown point and influence functon of an estimator, it demonstrates the technique of expressing an estimator as a descriptive measure from which its influence function can be derived and then used to explore the efficiency and robustness properties of the estimator. Mathematical techniques are complemented by computational algorithms and Minitab macros for finding bootstrap and influence function estimates of standard errors of the estimators, robust confidence intervals, robust regression estimates and their standard errors. Includes examples and problems.

Robust Linear Regression in Replicated Measurement Error Models

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Publisher :
ISBN 13 :
Total Pages : 26 pages
Book Rating : 4.:/5 (13 download)

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Book Synopsis Robust Linear Regression in Replicated Measurement Error Models by : Raymond J. Carroll

Download or read book Robust Linear Regression in Replicated Measurement Error Models written by Raymond J. Carroll and published by . This book was released on 1990 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose robust and bounded influence methods for linear regression when some of the predictors are measured with error. We address the important special case that the surrogate predictors are replicated. The robust methods proposed are variants of the so-called Mallows class of estimates. The resulting estimators are easily computed and have a simple asymptotic theory. An example is used to illustrate the results.

Identification of Continuous-Time Systems

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Publisher : CRC Press
ISBN 13 : 1000732622
Total Pages : 143 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Identification of Continuous-Time Systems by : Allamaraju Subrahmanyam

Download or read book Identification of Continuous-Time Systems written by Allamaraju Subrahmanyam and published by CRC Press. This book was released on 2019-12-06 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt: Models of dynamical systems are required for various purposes in the field of systems and control. The models are handled either in discrete time (DT) or in continuous time (CT). Physical systems give rise to models only in CT because they are based on physical laws which are invariably in CT. In system identification, indirect methods provide DT models which are then converted into CT. Methods of directly identifying CT models are preferred to the indirect methods for various reasons. The direct methods involve a primary stage of signal processing, followed by a secondary stage of parameter estimation. In the primary stage, the measured signals are processed by a general linear dynamic operation—computational or realized through prefilters, to preserve the system parameters in their native CT form—and the literature is rich on this aspect. In this book: Identification of Continuous-Time Systems-Linear and Robust Parameter Estimation, Allamaraju Subrahmanyam and Ganti Prasada Rao consider CT system models that are linear in their unknown parameters and propose robust methods of estimation. This book complements the existing literature on the identification of CT systems by enhancing the secondary stage through linear and robust estimation. In this book, the authors provide an overview of CT system identification, consider Markov-parameter models and time-moment models as simple linear-in-parameters models for CT system identification, bring them into mainstream model parameterization via basis functions, present a methodology to robustify the recursive least squares algorithm for parameter estimation of linear regression models, suggest a simple off-line error quantification scheme to show that it is possible to quantify error even in the absence of informative priors, and indicate some directions for further research. This modest volume is intended to be a useful addition to the literature on identifying CT systems.

Robustness in Statistics

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ISBN 13 :
Total Pages : 330 pages
Book Rating : 4.:/5 (319 download)

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Book Synopsis Robustness in Statistics by : Robert L. Launer

Download or read book Robustness in Statistics written by Robert L. Launer and published by . This book was released on 1979 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to robust estimation; The robustness of residual displays; Robust smoothing; Robust pitman-like estimators; Robust estimation in the presence of outliers; Study of robustness by simulation: particularly improvement by adjustment and combination; Robust techniques for the user; Application of robust regression to trajectory data reduction; Tests for censoring of extreme values (especially) when population distributions are incompletely defined; Robust estimation for time series autoregressions; Robust techniques in communication; Robustness in the strategy of scientific model building; A density-quantile function perspective on robust.

Random Sample Consensus

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Publisher : One Billion Knowledgeable
ISBN 13 :
Total Pages : 155 pages
Book Rating : 4.:/5 (661 download)

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Book Synopsis Random Sample Consensus by : Fouad Sabry

Download or read book Random Sample Consensus written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2024-04-30 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is Random Sample Consensus Random sample consensus, also known as RANSAC, is an iterative method that is used to estimate the parameters of a mathematical model based on a collection of observed data that includes outliers. This method is used in situations where the outliers are permitted to have no impact on the values of the estimates. The conclusion is that it is also possible to view it as a tool for detecting outliers. An algorithm is considered to be non-deterministic if it is able to generate a suitable result only with a certain probability, and this likelihood increases as the number of iterations that are permitted via the method increases. In 1981, Fischler and Bolles, who were working at SRI International, were the ones who initially published the algorithm. In order to solve the Location Determination Problem (LDP), which is a problem in which the objective is to find the points in space that project onto an image and then convert those points into a set of landmarks with known positions, they utilized RANSAC. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Random sample consensus Chapter 2: Estimator Chapter 3: Least squares Chapter 4: Outlier Chapter 5: Cross-validation (statistics) Chapter 6: Errors and residuals Chapter 7: Mixture model Chapter 8: Robust statistics Chapter 9: Image stitching Chapter 10: Resampling (statistics) (II) Answering the public top questions about random sample consensus. (III) Real world examples for the usage of random sample consensus in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Random Sample Consensus.

Handbook of Measurement Error Models

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Publisher : CRC Press
ISBN 13 : 1351588591
Total Pages : 648 pages
Book Rating : 4.3/5 (515 download)

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Book Synopsis Handbook of Measurement Error Models by : Grace Y. Yi

Download or read book Handbook of Measurement Error Models written by Grace Y. Yi and published by CRC Press. This book was released on 2021-09-28 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: Measurement error arises ubiquitously in applications and has been of long-standing concern in a variety of fields, including medical research, epidemiological studies, economics, environmental studies, and survey research. While several research monographs are available to summarize methods and strategies of handling different measurement error problems, research in this area continues to attract extensive attention. The Handbook of Measurement Error Models provides overviews of various topics on measurement error problems. It collects carefully edited chapters concerning issues of measurement error and evolving statistical methods, with a good balance of methodology and applications. It is prepared for readers who wish to start research and gain insights into challenges, methods, and applications related to error-prone data. It also serves as a reference text on statistical methods and applications pertinent to measurement error models, for researchers and data analysts alike. Features: Provides an account of past development and modern advancement concerning measurement error problems Highlights the challenges induced by error-contaminated data Introduces off-the-shelf methods for mitigating deleterious impacts of measurement error Describes state-of-the-art strategies for conducting in-depth research

Measurement Error in Nonlinear Models

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Publisher : CRC Press
ISBN 13 : 1420010131
Total Pages : 484 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Measurement Error in Nonlinear Models by : Raymond J. Carroll

Download or read book Measurement Error in Nonlinear Models written by Raymond J. Carroll and published by CRC Press. This book was released on 2006-06-21 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: It's been over a decade since the first edition of Measurement Error in Nonlinear Models splashed onto the scene, and research in the field has certainly not cooled in the interim. In fact, quite the opposite has occurred. As a result, Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition has been revamped and ex

Optimal and Robust Estimation

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Publisher : CRC Press
ISBN 13 : 1420008293
Total Pages : 546 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Optimal and Robust Estimation by : Frank L. Lewis

Download or read book Optimal and Robust Estimation written by Frank L. Lewis and published by CRC Press. This book was released on 2017-12-19 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: More than a decade ago, world-renowned control systems authority Frank L. Lewis introduced what would become a standard textbook on estimation, under the title Optimal Estimation, used in top universities throughout the world. The time has come for a new edition of this classic text, and Lewis enlisted the aid of two accomplished experts to bring the book completely up to date with the estimation methods driving today's high-performance systems. A Classic Revisited Optimal and Robust Estimation: With an Introduction to Stochastic Control Theory, Second Edition reflects new developments in estimation theory and design techniques. As the title suggests, the major feature of this edition is the inclusion of robust methods. Three new chapters cover the robust Kalman filter, H-infinity filtering, and H-infinity filtering of discrete-time systems. Modern Tools for Tomorrow's Engineers This text overflows with examples that highlight practical applications of the theory and concepts. Design algorithms appear conveniently in tables, allowing students quick reference, easy implementation into software, and intuitive comparisons for selecting the best algorithm for a given application. In addition, downloadable MATLAB® code allows students to gain hands-on experience with industry-standard software tools for a wide variety of applications. This cutting-edge and highly interactive text makes teaching, and learning, estimation methods easier and more modern than ever.

Robust Estimation for the Errors-in-variables Model

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Publisher :
ISBN 13 :
Total Pages : 354 pages
Book Rating : 4.:/5 (132 download)

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Book Synopsis Robust Estimation for the Errors-in-variables Model by : Ruben Horacio Zamar

Download or read book Robust Estimation for the Errors-in-variables Model written by Ruben Horacio Zamar and published by . This book was released on 1985 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: