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Author : Edward L. Price
Publisher :
ISBN 13 :
Total Pages : 196 pages
Book Rating : 4.:/5 (37 download)
Download or read book Robust Estimation by Stochastic Approximation and Error Models for Robust Procedures written by Edward L. Price and published by . This book was released on 1977 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :
Publisher :
ISBN 13 :
Total Pages : 556 pages
Book Rating : 4.F/5 ( download)
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1993 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Daniel Merlyn Goodfellow
Publisher :
ISBN 13 :
Total Pages : 436 pages
Book Rating : 4.:/5 (228 download)
Download or read book Robust Estimation of Location and Scale Via Stochastic Approximation written by Daniel Merlyn Goodfellow and published by . This book was released on 1977 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Frank L. Lewis
Publisher : CRC Press
ISBN 13 : 1351837540
Total Pages : 638 pages
Book Rating : 4.3/5 (518 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 638 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 : Robert L. Launer
Publisher : Academic Press
ISBN 13 : 1483263363
Total Pages : 313 pages
Book Rating : 4.4/5 (832 download)
Download or read book Robustness in Statistics written by Robert L. Launer and published by Academic Press. This book was released on 2014-05-12 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robustness in Statistics contains the proceedings of a Workshop on Robustness in Statistics held on April 11-12, 1978, at the Army Research Office in Research Triangle Park, North Carolina. The papers review the state of the art in statistical robustness and cover topics ranging from robust estimation to the robustness of residual displays and robust smoothing. The application of robust regression to trajectory data reduction is also discussed. Comprised of 14 chapters, this book begins with an introduction to robust estimation, paying particular attention to iteration schemes and error structure of estimators. Sensitivity and influence curves as well as their connection with jackknife estimates are described. The reader is then introduced to a simple analog of trimmed means that can be used for studying residuals from a robust point-of-view; a class of robust estimators (called P-estimators) based on the location and scale-invariant Pitman estimators of location; and robust estimation in the presence of outliers. Subsequent chapters deal with robust regression and its use to reduce trajectory data; tests for censoring of extreme values, especially when population distributions are incompletely defined; and robust estimation for time series autoregressions. This monograph should be of interest to mathematicians and statisticians.
Author : Werner Stahel
Publisher : Springer Science & Business Media
ISBN 13 : 1461244447
Total Pages : 384 pages
Book Rating : 4.4/5 (612 download)
Download or read book Directions in Robust Statistics and Diagnostics written by Werner Stahel and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: This IMA Volume in Mathematics and its Applications DIRECTIONS IN ROBUST STATISTICS AND DIAGNOSTICS is based on the proceedings of the first four weeks of the six week IMA 1989 summer program "Robustness, Diagnostics, Computing and Graphics in Statistics". An important objective of the organizers was to draw a broad set of statisticians working in robustness or diagnostics into collaboration on the challenging problems in these areas, particularly on the interface between them. We thank the organizers of the robustness and diagnostics program Noel Cressie, Thomas P. Hettmansperger, Peter J. Huber, R. Douglas Martin, and especially Werner Stahel and Sanford Weisberg who edited the proceedings. A vner Friedman Willard Miller, Jr. PREFACE Central themes of all statistics are estimation, prediction, and making decisions under uncertainty. A standard approach to these goals is through parametric mod elling. Parametric models can give a problem sufficient structure to allow standard, well understood paradigms to be applied to make the required inferences. If, how ever, the parametric model is not completely correct, then the standard inferential methods may not give reasonable answers. In the last quarter century, particularly with the advent of readily available computing, more attention has been paid to the problem of inference when the parametric model used is not correctly specified.
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 :
Publisher :
ISBN 13 :
Total Pages : 780 pages
Book Rating : 4.:/5 (31 download)
Download or read book Proceedings written by and published by . This book was released on 1977 with total page 780 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : David C. Hoaglin
Publisher : John Wiley & Sons
ISBN 13 : 0471384917
Total Pages : 484 pages
Book Rating : 4.4/5 (713 download)
Download or read book Understanding Robust and Exploratory Data Analysis written by David C. Hoaglin and published by John Wiley & Sons. This book was released on 2000-06-02 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: Originally published in hardcover in 1982, this book is now offered in a Wiley Classics Library edition. A contributed volume, edited by some of the preeminent statisticians of the 20th century, Understanding of Robust and Exploratory Data Analysis explains why and how to use exploratory data analysis and robust and resistant methods in statistical practice.
Author : David F. Andrews
Publisher : Princeton University Press
ISBN 13 : 1400867010
Total Pages : 384 pages
Book Rating : 4.4/5 (8 download)
Download or read book Robust Estimates of Location written by David F. Andrews and published by Princeton University Press. This book was released on 2015-03-08 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Because estimation involves inferring information about an unknown quantity on the basis of available data, the selection of an estimator is influenced by its ability to perform well under the conditions that are assumed to underlie the data. Since these conditions are never known exactly, the estimators chosen must be robust; i.e., they must be able to perform well under a variety of underlying conditions. The theory of robust estimation is based on specified properties of specified estimators under specified conditions. This book was written as the result of a study undertaken to establish the interaction of these three components over as large a range as possible. Originally published in 1972. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
Author : Sanjoy K. Mitter
Publisher :
ISBN 13 :
Total Pages : 25 pages
Book Rating : 4.:/5 (281 download)
Download or read book Point Estimation, Stochastic Approximation, and Robust Kalman Filtering written by Sanjoy K. Mitter and published by . This book was released on 1993 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :
Publisher :
ISBN 13 :
Total Pages : 320 pages
Book Rating : 4.X/5 (2 download)
Download or read book Proceedings of the Joint Automatic Control Conference written by and published by . This book was released on 1978 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :
Publisher :
ISBN 13 :
Total Pages : 594 pages
Book Rating : 4.:/5 (31 download)
Download or read book Proceedings of the ... Conference on Information Sciences and Systems written by and published by . This book was released on 1978 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 : 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 : 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.
