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A Monte Carlo Study Of Robust Estimators Of Location
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Book Synopsis A Monte Carlo Study of Robust Estimators of Location by : Raymond J. Carroll
Download or read book A Monte Carlo Study of Robust Estimators of Location written by Raymond J. Carroll and published by . This book was released on 1975 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: Andrews et al (1972) carried out an extensive Monte Carlo study of robust estimators of location. Their conclusions were that the hampel and the skipped estimates, as classes, seemed to be preferable to some of the other currently fashionable estimators. The present study extends this work to include estimators not previously examined. The estimators are compared over short-tailed as well as long-tailed alternatives and also over some dependent data generated by first-order autoregressive schemes. The conclusions of the present study are threefold. First, from our limited study, none of the so-called robust estimators are very robust over short-tailed situations. More work seems to be necessary in this situation. Second, none of the estimators perform very well in dependent data situations, particularly when the correlation is large and positive. This seems to be a rather pressing problem. Finally, for long-tailed alternatives, the hampel estimators and Hogg-type adaptive versions of the hampels are the strongest classes.
Book Synopsis A Monte Carlo Study of Robust Estimators of Correlation by : Peter Ratener
Download or read book A Monte Carlo Study of Robust Estimators of Correlation written by Peter Ratener and published by . This book was released on 1977 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis An Interim Report of a Monte Carlo Study of Robust Estimators of Width by : David A. Lax
Download or read book An Interim Report of a Monte Carlo Study of Robust Estimators of Width written by David A. Lax and published by . This book was released on 1975 with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Monte Carlo Techniques in Studying Robust Estimators by : David C. Hoaglin
Download or read book Monte Carlo Techniques in Studying Robust Estimators written by David C. Hoaglin and published by . This book was released on 2010 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent work on robust estimation has led to many procedures, which are easy to formulate and straightforward to program but difficult to study analytically. In such circumstances experimental sampling is quite attractive, but the variety and complexity of both estimators and sampling situations make effective Monte Carlo techniques essential. This discussion examines problems, techniques, and results and draws on examples in studies of robust location and robust regression.
Book Synopsis A Monte Carlo Study of Robust Location Estimates with Non-Gaussian Multivariate Data by : M. Anthony Wong
Download or read book A Monte Carlo Study of Robust Location Estimates with Non-Gaussian Multivariate Data written by M. Anthony Wong and published by . This book was released on 1980 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Widthing Monte Carlo Program: a Computer Program for a Monte Carlo Study on Robust Estimators on Width by : D. A. Lax
Download or read book The Widthing Monte Carlo Program: a Computer Program for a Monte Carlo Study on Robust Estimators on Width written by D. A. Lax and published by . This book was released on 1975 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Estimates of Location by : David F. Andrews
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.
Book Synopsis The Widthing Monte Carlo Program by : David A. Lax
Download or read book The Widthing Monte Carlo Program written by David A. Lax and published by . This book was released on 1975 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Monte Carlo for Robust Regression by : Paul W. Holland
Download or read book Monte Carlo for Robust Regression written by Paul W. Holland and published by . This book was released on 1973 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper gives an alternative derivation of a Monte Carlo method that has been used to study robust estimators. Extensions of the technique to the regression case are also considered and some computational points are briefly mentioned.
Book Synopsis Robust Estimation Techniques for Location Parameter Estimation of Symmetric Distributions by :
Download or read book Robust Estimation Techniques for Location Parameter Estimation of Symmetric Distributions written by and published by . This book was released on 1972 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: Several robust estimators are considered for analysis and explanation. Monte Carlo techniques are used to investigate the efficiency of these robust estimators relative to the best estimator for the distribution under consideration. Sample sizes of 12 and 24 were drawn 4200 times from five symmetric probability distributions. The results show that over a class of distributions the robust estimators provide a higher guaranteed efficiency than the best estimator for any particular distribution in the family. Some interesting results are apparent from an analysis of the graphs in Appendix C indicating some upper bounds on the size of the Monte Carlo sample when conducting this type of study.
Book Synopsis A Monte Carlo study of two robust alternatives to least squares regression estimation by :
Download or read book A Monte Carlo study of two robust alternatives to least squares regression estimation written by and published by . This book was released on 1974 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Estimation of Location and Scale Parameters by : Loren W. Jorgenson
Download or read book Robust Estimation of Location and Scale Parameters written by Loren W. Jorgenson and published by . This book was released on 1973 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Monte Carlo analysis was performed to determine the efficiency of the Harter robust estimators of the scale and location parameters of double exponential, normal, and uniform distributions relative to the maximum-likelihood estimators. Two modifications were made to the Harter estimators which increased the relative efficiency except when the underlying population was uniformly distributed. The modified estimators were then designated the Moore estimators and the Jorgenson estimators. Tables were prepared comparing the relative efficiencies of the Harter, Jorgenson, Moore, Hogg, Hodges-Lehmann, and the Switzer robust estimators of the location parameter for the double exponential, the normal, and the uniform distributions for samples of size 12 and 24. Two types of figure of merit were defined for a robust estimator. The choice of the best robust estimator is a function of sample size and the criteria used. (Author).
Book Synopsis The Widthing Monte Carlo Program by : David A. Lax
Download or read book The Widthing Monte Carlo Program written by David A. Lax and published by . This book was released on 1975 with total page 0 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 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 2011-12-14 with total page 713 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 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 A Monte Carlo Study of Two Robust Alternatives of Least Square Regression Estimation by : Paul W. Holland
Download or read book A Monte Carlo Study of Two Robust Alternatives of Least Square Regression Estimation written by Paul W. Holland and published by . This book was released on 1974 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We give some Monte Carlo results on the performance of two robust alternatives to least squares regression estimation - least absolute residuals and the one-step "sine" estimator. We show how to scale the residuals for the sine estimator to achieve constant efficiency at the Gaussian across various choices of X-matrix and give some results for the contaminated Gaussian distribution
