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Author : Qiong Wang
Publisher :
ISBN 13 :
Total Pages : 91 pages
Book Rating : 4.:/5 (623 download)
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.
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.
Author : Joseph H. R. Croos
Publisher :
ISBN 13 :
Total Pages : 284 pages
Book Rating : 4.:/5 (27 download)
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:
Author : Fouad Sabry
Publisher : One Billion Knowledgeable
ISBN 13 :
Total Pages : 155 pages
Book Rating : 4.:/5 (661 download)
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.
Author : Frank L. Lewis
Publisher : CRC Press
ISBN 13 : 1420008293
Total Pages : 546 pages
Book Rating : 4.4/5 (2 download)
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.
Author : Hans Nyquist
Publisher :
ISBN 13 :
Total Pages : 24 pages
Book Rating : 4.:/5 (185 download)
Download or read book Robust Estimation of the Structural Errors-in-variables Model written by Hans Nyquist and published by . This book was released on 1985 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Allamaraju Subrahmanyam
Publisher : CRC Press
ISBN 13 : 1000732622
Total Pages : 143 pages
Book Rating : 4.0/5 (7 download)
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.
Author : Ruben Horacio Zamar
Publisher :
ISBN 13 :
Total Pages : 354 pages
Book Rating : 4.:/5 (132 download)
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:
Author : Rand R. Wilcox
Publisher : Academic Press
ISBN 13 : 0123869838
Total Pages : 713 pages
Book Rating : 4.1/5 (238 download)
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"--
Author : John P. Buonaccorsi
Publisher : CRC Press
ISBN 13 : 1420066587
Total Pages : 465 pages
Book Rating : 4.4/5 (2 download)
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
Author : Pavel Cizek
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)
Download or read book Robust Estimation with Discrete Explanatory Variables written by Pavel Cizek and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The least squares estimator is probably the most frequently used estimation method in regression analysis. Unfortunately, it is also quite sensitive to data contamination and model misspecification. Although there are several robust estimators designed for parametric regression models that can be used in place of least squares, these robust estimators cannot be easily applied to models containing binary and categorical explanatory variables. Therefore, I design a robust estimator that can be used for any linear regression model no matter what kind of explanatory variables the model contains. Additionally, I propose an adaptive procedure that maximizes the efficiency of the proposed estimator for a given data set while preserving its robustness.
Author : Philip J. Brown
Publisher : American Mathematical Soc.
ISBN 13 : 0821851179
Total Pages : 262 pages
Book Rating : 4.8/5 (218 download)
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.
Author : Frank R. Hampel
Publisher :
ISBN 13 :
Total Pages : 230 pages
Book Rating : 4.F/5 ( download)
Download or read book Contributions to the Theory of Robust Estimation written by Frank R. Hampel and published by . This book was released on 1968 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :
Publisher :
ISBN 13 :
Total Pages : 702 pages
Book Rating : 4.:/5 (31 download)
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1995 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Daniel W. Schafer
Publisher :
ISBN 13 :
Total Pages : 29 pages
Book Rating : 4.:/5 (13 download)
Download or read book Measurement Error Model Estimation Using Iteratively Weighted Least Squares written by Daniel W. Schafer and published by . This book was released on 1989 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Michael Bosse
Publisher :
ISBN 13 : 9781680832143
Total Pages : 58 pages
Book Rating : 4.8/5 (321 download)
Download or read book Robust Estimation and Applications in Robotics written by Michael Bosse and published by . This book was released on 2016-12-20 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solving estimation problems is a fundamental component of numerous robotics applications. Prominent examples involve pose estimation, point cloud alignment, and object tracking. Algorithms for solving these estimation problems need to cope with new challenges due to an increased use of potentially poor low-cost sensors, and an ever growing deployment of robotic algorithms in consumer products, which operate in potentially unknown environments. These algorithms need to be capable of being robust against strong nonlinearities, high uncertainty levels, and numerous outliers. However, particularly in robotics, the Gaussian assumption is prevalent in solutions to multivariate parameter estimation problems without providing the desired level of robustness. Robust Estimation and Applications in Robotics sets out to address the aforementioned challenges by providing an introduction to robust estimation with a particular focus on robotics. It starts by providing a concise overview of the theory of M-estimation. M-estimators share many of the convenient properties of least-squares estimators, and at the same time are much more robust to deviations from the Gaussian model assumption. It goes on to present several example applications where M-Estimation is used to increase robustness against nonlinearities and outliers. Robust Estimation and Applications in Robotics is an ideal introduction to robust statistics that only requires preliminary knowledge of probability theory. It also includes examples of robotics applications where robust statistical tools make a difference.
Author : David Birkes
Publisher : John Wiley & Sons
ISBN 13 : 1118150244
Total Pages : 248 pages
Book Rating : 4.1/5 (181 download)
Download or read book Alternative Methods of Regression written by David Birkes and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Of related interest. Nonlinear Regression Analysis and its Applications Douglas M. Bates and Donald G. Watts ".an extraordinary presentation of concepts and methods concerning the use and analysis of nonlinear regression models.highly recommend[ed].for anyone needing to use and/or understand issues concerning the analysis of nonlinear regression models." --Technometrics This book provides a balance between theory and practice supported by extensive displays of instructive geometrical constructs. Numerous in-depth case studies illustrate the use of nonlinear regression analysis--with all data sets real. Topics include: multi-response parameter estimation; models defined by systems of differential equations; and improved methods for presenting inferential results of nonlinear analysis. 1988 (0-471-81643-4) 365 pp. Nonlinear Regression G. A. F. Seber and C. J. Wild ".[a] comprehensive and scholarly work.impressively thorough with attention given to every aspect of the modeling process." --Short Book Reviews of the International Statistical Institute In this introduction to nonlinear modeling, the authors examine a wide range of estimation techniques including least squares, quasi-likelihood, and Bayesian methods, and discuss some of the problems associated with estimation. The book presents new and important material relating to the concept of curvature and its growing role in statistical inference. It also covers three useful classes of models --growth, compartmental, and multiphase --and emphasizes the limitations involved in fitting these models. Packed with examples and graphs, it offers statisticians, statistical consultants, and statistically oriented research scientists up-to-date access to their fields. 1989 (0-471-61760-1) 768 pp. Mathematical Programming in Statistics T. S. Arthanari and Yadolah Dodge "The authors have achieved their stated intention.in an outstanding and useful manner for both students and researchers.Contains a superb synthesis of references linked to the special topics and formulations by a succinct set of bibliographical notes.Should be in the hands of all system analysts and computer system architects." --Computing Reviews This unique book brings together most of the available results on applications of mathematical programming in statistics, and also develops the necessary statistical and programming theory and methods. 1981 (0-471-08073-X) 413 pp.
