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Robust Estimates Of Ordered Parameters
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Book Synopsis Robust Estimates of Ordered Parameters by : Rhonda Magel
Download or read book Robust Estimates of Ordered Parameters written by Rhonda Magel and published by . This book was released on 1982 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authors the estimation of a collection of location parameters when it is believed, a priori, that their ordering is known. The least squares and least absolute deviations estimates subject to this ordering restriction have been studied in the literature. They seek robust estimators which perform well for a broad range of distributions. The results of a Monte Carlo study and a study of computation algorithms are discussed.
Book Synopsis Breakthroughs in Statistics by : Samuel Kotz
Download or read book Breakthroughs in Statistics written by Samuel Kotz and published by Springer Science & Business Media. This book was released on 2013-12-01 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volume III includes more selections of articles that have initiated fundamental changes in statistical methodology. It contains articles published before 1980 that were overlooked in the previous two volumes plus articles from the 1980's - all of them chosen after consulting many of today's leading statisticians.
Book Synopsis Modeling Ordered Choices by : William H. Greene
Download or read book Modeling Ordered Choices written by William H. Greene and published by Cambridge University Press. This book was released on 2010-04-08 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is increasingly common for analysts to seek out the opinions of individuals and organizations using attitudinal scales such as degree of satisfaction or importance attached to an issue. Examples include levels of obesity, seriousness of a health condition, attitudes towards service levels, opinions on products, voting intentions, and the degree of clarity of contracts. Ordered choice models provide a relevant methodology for capturing the sources of influence that explain the choice made amongst a set of ordered alternatives. The methods have evolved to a level of sophistication that can allow for heterogeneity in the threshold parameters, in the explanatory variables (through random parameters), and in the decomposition of the residual variance. This book brings together contributions in ordered choice modeling from a number of disciplines, synthesizing developments over the last fifty years, and suggests useful extensions to account for the wide range of sources of influence on choice.
Book Synopsis An Uniformly Asymptotically Efficient Robust Estimator of a Location Parameter (Classic Reprint) by : Kei Takeuchi
Download or read book An Uniformly Asymptotically Efficient Robust Estimator of a Location Parameter (Classic Reprint) written by Kei Takeuchi and published by Forgotten Books. This book was released on 2018-02-22 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt: Excerpt from An Uniformly Asymptotically Efficient Robust Estimator of a Location Parameter The basic idea of the method is as follows. Although it is quite impossible to estimate the variance covariance matrix of the order statistics directly from the sample, it is possible to estimate the variance-covariance of the order statistics of a sample of size k, from a sample of size n, and if n is appreciably larger than k, the estimates would be accurate. But if the distribution is regular, this information about the variance - covariance matrix of the order statistics of a sample of size k can be effectively used to construct a nearly efficient estimator based on the sample of size n provided that k is also large. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.
Book Synopsis Robustness in Statistics by : Robert L. Launer
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.
Book Synopsis Robust Statistical Procedures by : Jana Jurecková
Download or read book Robust Statistical Procedures written by Jana Jurecková and published by John Wiley & Sons. This book was released on 1996-04-19 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: A broad and unified methodology for robust statistics—with exciting new applications Robust statistics is one of the fastest growing fields in contemporary statistics. It is also one of the more diverse and sometimes confounding areas, given the many different assessments and interpretations of robustness by theoretical and applied statisticians. This innovative book unifies the many varied, yet related, concepts of robust statistics under a sound theoretical modulation. It seamlessly integrates asymptotics and interrelations, and provides statisticians with an effective system for dealing with the interrelations between the various classes of procedures. Drawing on the expertise of researchers from around the world, and covering over a decade's worth of developments in the field, Robust Statistical Procedures: Asymptotics and Interrelations: Discusses both theory and applications in its two parts, from the fundamentals to robust statistical inference Thoroughly explores the interrelations between diverse classes of procedures, unlike any other book Compares nonparametric procedures with robust statistics, explaining in detail asymptotic representations for various estimators Provides a timesaving list of mathematical tools for the problems under discussion Keeps mathematical abstractions to a minimum, in spite of its largely theoretical content Includes useful problems and exercises at the end of each chapter Offers strategies for more complex models when using robust statistical procedures Self-contained and rounded in approach, this book is invaluable for both applied statisticians and theoretical researchers; for graduate students in mathematical statistics; and for anyone interested in the influence of this methodology.
Book Synopsis Robust Estimation of the Location Parameter of Life Distributions by : Linda M. Allen
Download or read book Robust Estimation of the Location Parameter of Life Distributions written by Linda M. Allen and published by . This book was released on 1985 with total page 59 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis determined that for time to failure distributions that are moderate deviations from the negative exponential distribution, a robust estimate of the minimum life could be arrived at by assuming the underlying distribution was exponential and using the minimum variance, unbiased, maximum likelihood estimator. It was found that estimators using the minimum distance statistics of Kolmogorov, Cramer-von Mises, and Anderson-Darling did not perform well with the asymmetric distributions explored in this thesis. However, they may still prove useful for life distributions with larger shape parameters. The analysis was accomplished by using Monte Carlo techniques to generate random samples of time to failure data from specific distributions, and using this empirical data to estimate the actual minimum life of the distribution. Five estimators were explored: the minimum variance, unbiased, maximum likelihood estimator of the two-parameter negative exponential distribution; the first ordered statistic; and the three minimum distance methods. The performance of these estimators was evaluated by comparing their mean square errors with the mean square error of the chosen best estimator.
Book Synopsis Robust Estimation and Hypothesis Testing by : Moti Lal Tiku
Download or read book Robust Estimation and Hypothesis Testing written by Moti Lal Tiku and published by New Age International. This book was released on 2004 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt: In statistical theory and practice, a certain distribution is usually assumed and then optimal solutions sought. Since deviations from an assumed distribution are very common, one cannot feel comfortable with assuming a particular distribution and believing it to be exactly correct. That brings the robustness issue in focus. In this book, we have given statistical procedures which are robust to plausible deviations from an assumed mode. The method of modified maximum likelihood estimation is used in formulating these procedures. The modified maximum likelihood estimators are explicit functions of sample observations and are easy to compute. They are asymptotically fully efficient and are as efficient as the maximum likelihood estimators for small sample sizes. The maximum likelihood estimators have computational problems and are, therefore, elusive. A broad range of topics are covered in this book. Solutions are given which are easy to implement and are efficient. The solutions are also robust to data anomalies: outliers, inliers, mixtures and data contaminations. Numerous real life applications of the methodology are given.
Book Synopsis Methodology in Robust and Nonparametric Statistics by : Jana Jureckova
Download or read book Methodology in Robust and Nonparametric Statistics written by Jana Jureckova and published by CRC Press. This book was released on 2012-07-20 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robust and nonparametric statistical methods have their foundation in fields ranging from agricultural science to astronomy, from biomedical sciences to the public health disciplines, and, more recently, in genomics, bioinformatics, and financial statistics. These disciplines are presently nourished by data mining and high-level computer-based algo
Download or read book NBS Special Publication written by and published by . This book was released on 1970 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 2005-01-05 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: This revised book provides a thorough explanation of the foundation of robust methods, incorporating the latest updates on R and S-Plus, robust ANOVA (Analysis of Variance) and regression. It guides advanced students and other professionals through the basic strategies used for developing practical solutions to problems, and provides a brief background on the foundations of modern methods, placing the new methods in historical context. Author Rand Wilcox includes chapter exercises and many real-world examples that illustrate how various methods perform in different situations. Introduction to Robust Estimation and Hypothesis Testing, Second Edition, focuses on the practical applications of modern, robust methods which can greatly enhance our chances of detecting true differences among groups and true associations among variables. * Covers latest developments in robust regression * Covers latest improvements in ANOVA * Includes newest rank-based methods * Describes and illustrated easy to use software
Book Synopsis Contributions to the Theory of Robust Estimation by : Frank R. Hampel
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:
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.
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.
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"--
Book Synopsis Robust and Nonlinear Time Series Analysis by : J. Franke
Download or read book Robust and Nonlinear Time Series Analysis written by J. Franke and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Classical time series methods are based on the assumption that a particular stochastic process model generates the observed data. The, most commonly used assumption is that the data is a realization of a stationary Gaussian process. However, since the Gaussian assumption is a fairly stringent one, this assumption is frequently replaced by the weaker assumption that the process is wide~sense stationary and that only the mean and covariance sequence is specified. This approach of specifying the probabilistic behavior only up to "second order" has of course been extremely popular from a theoretical point of view be cause it has allowed one to treat a large variety of problems, such as prediction, filtering and smoothing, using the geometry of Hilbert spaces. While the literature abounds with a variety of optimal estimation results based on either the Gaussian assumption or the specification of second-order properties, time series workers have not always believed in the literal truth of either the Gaussian or second-order specifica tion. They have none-the-less stressed the importance of such optimali ty results, probably for two main reasons: First, the results come from a rich and very workable theory. Second, the researchers often relied on a vague belief in a kind of continuity principle according to which the results of time series inference would change only a small amount if the actual model deviated only a small amount from the assum ed model.
Book Synopsis Robust Techniques to Estimate Parameters of Linear Models by : Neelesh Pandey
Download or read book Robust Techniques to Estimate Parameters of Linear Models written by Neelesh Pandey and published by . This book was released on 2020 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt: Standard regression technique uses Ordinary Least Square estimator (OLS) for model fitting. In the presence of outliers OLS fits the model vary sharply with respect to actual regression curve. For model fitting, this paper applies robust estimation approach as a substitute for OLS. This approach reduces the ill effect of outliers and learns the representation of data. Various robust regression techniques, namely, L estimators, M estimators, S estimator and MM estimator have been used which works on the principle of order statistics and weighting techniques to reduce the weight of distant observations. These estimators are applied on four data set out of which 3 are taken from UCI repository and one is taken from NASA Surface meteorology and Solar energy. When comparing the methods on the basis of bias and variance parameters MM estimator performs well in majority of the data set while in some cases M estimator also exhibited promising results.
