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Robust Estimation Technique And Robust Autocorrelation Diagnostic For Multiple Linear Regression Model With Autocorrelated Errors
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Book Synopsis Robust Estimation Technique and Robust Autocorrelation Diagnostic for Multiple Linear Regression Model with Autocorrelated Errors by : Hock Ann Lim
Download or read book Robust Estimation Technique and Robust Autocorrelation Diagnostic for Multiple Linear Regression Model with Autocorrelated Errors written by Hock Ann Lim and published by . This book was released on 2014 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Estimation Methods and Robust Multicollinearity Diagnostics for Multiple Regression Model in the Presence of High Leverage Collinearity-influential Observations by : Arezoo Bagheri
Download or read book Robust Estimation Methods and Robust Multicollinearity Diagnostics for Multiple Regression Model in the Presence of High Leverage Collinearity-influential Observations written by Arezoo Bagheri and published by . This book was released on 2011 with total page 650 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Methods in Regression Analysis – Theory and Application by : Robert Finger
Download or read book Robust Methods in Regression Analysis – Theory and Application written by Robert Finger and published by GRIN Verlag. This book was released on 2007-05-06 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diploma Thesis from the year 2006 in the subject Mathematics - Statistics, grade: 1.3, European University Viadrina Frankfurt (Oder) (Wirtschaftswissenschaftliche Fakultät), language: English, abstract: Regression Analysis is an important statistical tool for many applications. The most frequently used approach to Regression Analysis is the method of Ordinary Least Squares. But this method is vulnerable to outliers; even a single outlier can spoil the estimation completely. How can this vulnerability be described by theoretical concepts and are there alternatives? This thesis gives an overview over concepts and alternative approaches. The three fundamental approaches to Robustness (qualitative-, infinitesimal- and quantitative Robustness) are introduced in this thesis and are applied to different estimators. The estimators under study are measures of location, scale and regression. The Robustness approaches are important for the theoretical judgement of certain estimators but as well for the development of alternatives to classical estimators. This thesis focuses on the (Robustness-) performance of estimators if outliers occur within the data set. Measures of location and scale provide necessary steppingstones into the topic of Regression Analysis. In particular the median and trimming approaches are found to produce very robust results. These results are used in Regression Analysis to find alternatives to the method of Ordinary Least Squares. Its vulnerability can be overcome by applying the methods of Least Median of Squares or Least Trimmed Squares. Different outlier diagnostic tools are introduced to improve the poor efficiency of these Regression Techniques. Furthermore, this thesis delivers a simulation of some Regression Techniques on different situations in Regression Analysis. This simulation focuses in particular on changes in regression estimates if outliers occur in the data. Theoretically derived results as well as the results of the simulation lead to the recommendation of the method of Reweighted Least Squares. Applying this method frequently on problems of Regression Analysis provides outlier resistant and efficient estimates.
Book Synopsis Robust Estimation with Discrete Explanatory Variables by : Pavel Cizek
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.
Book Synopsis Linear Regression Diagnostics by : Edwin Kuh
Download or read book Linear Regression Diagnostics written by Edwin Kuh and published by . This book was released on 1977 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper attempts to provide the user of linear multiple regression with a battery of diagnostic tools to determine which, if any, data points have high leverage or influence on the estimation process and how these possibly discrepant data points differ from the patterns set by the majority of the data. The point of view taken is that when diagnostics indicate the presence of anomolous data, the choice is open as to whether these data are in fact unusual and helpful, or possibly harmful and thus in need of modifications or deletion. The methodology developed depends on differences, derivatives, and decompositions of basic regression statistics. There is also a discussion of how these techniques can be used with robust and ridge estimators. An example is given showing the use of diagnostic methods in the estimation of a cross-country savings rate model
Book Synopsis Robust Regression and Outlier Detection by : Peter J. Rousseeuw
Download or read book Robust Regression and Outlier Detection written by Peter J. Rousseeuw and published by John Wiley & Sons. This book was released on 2003-10-03 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "The writing style is clear and informal, and much of the discussion is oriented to application. In short, the book is a keeper." –Mathematical Geology "I would highly recommend the addition of this book to the libraries of both students and professionals. It is a useful textbook for the graduate student, because it emphasizes both the philosophy and practice of robustness in regression settings, and it provides excellent examples of precise, logical proofs of theorems. . . .Even for those who are familiar with robustness, the book will be a good reference because it consolidates the research in high-breakdown affine equivariant estimators and includes an extensive bibliography in robust regression, outlier diagnostics, and related methods. The aim of this book, the authors tell us, is ‘to make robust regression available for everyday statistical practice.’ Rousseeuw and Leroy have included all of the necessary ingredients to make this happen." –Journal of the American Statistical Association
Book Synopsis A procedure for robust estimation and diagnostics in regression by : Daniel Peña
Download or read book A procedure for robust estimation and diagnostics in regression written by Daniel Peña and published by . This book was released on 1997 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Diagnostics and Robust Estimation When Transforming the Regression Model and the Responses by : R. J. Carroll
Download or read book Diagnostics and Robust Estimation When Transforming the Regression Model and the Responses written by R. J. Carroll and published by . This book was released on 1985 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: In regression analysis, the response is often transformed to remove heteroscedasticity and/or skewness. When a model already exists for the untransformed response, then it can be preserved by transforming both the model and the response with the same transformation. This methodology, is called transform both sides has been applied in several recent papers, and appears highly useful in practice. When a parametric transformation family such as power transformations is used, then the transformation can be estimated by maximum likelihood. The MLE however is very sensitive to outliers. This article proposes diagnostics which indicate cases influential for the transformation regression parameters. We also propose a robust bounded-influence estimator similar to the Krasker-Welsch regression estimate. Both diagnostics and the robust estimator can be implemented on standard software. (Author).
Book Synopsis Estimating the Autocorrelated Error Model with Trended Data, Further Results by : Rolla Edward Park
Download or read book Estimating the Autocorrelated Error Model with Trended Data, Further Results written by Rolla Edward Park and published by . This book was released on 1979 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Monte Carlo study is made of the small sample properties of various estimators of the linear regression model with first-order autocorrelated errors. When independent variables are trended, estimators using T transformed observations (Prais-Winsten) are much more efficient than those using T-1 (Cochrane-Orcutt). The best of the feasible estimators is iterated Prais-Winsten using a sum-of-squared-error minimizing estimate of the autocorrelation coefficient rho. None of the feasible estimators performs well in hypothesis testing; all seriously underestimate standard errors, making estimated coefficients appear to be much more significant than they actually are. (Author).
Book Synopsis Diagnostics and Robust Estimation When Transforming the Regression Model and the Response by : Raymond J. Carroll
Download or read book Diagnostics and Robust Estimation When Transforming the Regression Model and the Response written by Raymond J. Carroll and published by . This book was released on 1985 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: In regression analysis, the response is often transformed to remove heteroscedasticity and/or skewness. When a model already exists for the untransformed response, then it can be preserved by applying the same transform to both the model and the response. This methodology which we call 'transform both sides' has been applied in several recent papers, and appears highly useful in practice. When a parametric transformation family such as the power transformations is used, then the transformation can be estimated by maximum likelihood. The MLE, however, is very sensitive to outliers. This article proposes diagnostics to indicate cases influential for the transformation or regression parameters. Also proposed it a robust bounded-influence estimator similar to the Kraskeer-Welsch regression estimator. Keywords: Heteroscedasticity; Maximum likelihood. (Author).
Book Synopsis A Procedure for Robust Estimation and Diagnostics in Regression by : Daniel Peña
Download or read book A Procedure for Robust Estimation and Diagnostics in Regression written by Daniel Peña and published by . This book was released on 1996 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis New Methods and Comparative Evaluations for Robust and Biased- Robust Regression Estimation by : James Robert Simpson
Download or read book New Methods and Comparative Evaluations for Robust and Biased- Robust Regression Estimation written by James Robert Simpson and published by . This book was released on 1995 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Regression by : Kenneth D. Lawrence
Download or read book Robust Regression written by Kenneth D. Lawrence and published by Routledge. This book was released on 2019-05-20 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robust Regression: Analysis and Applications characterizes robust estimators in terms of how much they weight each observation discusses generalized properties of Lp-estimators. Includes an algorithm for identifying outliers using least absolute value criterion in regression modeling reviews redescending M-estimators studies Li linear regression proposes the best linear unbiased estimators for fixed parameters and random errors in the mixed linear model summarizes known properties of Li estimators for time series analysis examines ordinary least squares, latent root regression, and a robust regression weighting scheme and evaluates results from five different robust ridge regression estimators.
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 Robust Nonparametric Statistical Methods by : Thomas P. Hettmansperger
Download or read book Robust Nonparametric Statistical Methods written by Thomas P. Hettmansperger and published by CRC Press. This book was released on 2010-12-20 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting an extensive set of tools and methods for data analysis, Robust Nonparametric Statistical Methods, Second Edition covers univariate tests and estimates with extensions to linear models, multivariate models, times series models, experimental designs, and mixed models. It follows the approach of the first edition by developing rank-based m
Book Synopsis Robust Estimation for Multiple Linear Regression [with CD Copy]. by : Shashi Shekhar
Download or read book Robust Estimation for Multiple Linear Regression [with CD Copy]. written by Shashi Shekhar and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Combination of Biased and Robust Estimation Techniques in Multiple Regression Models by : Ronald Gene Askin
Download or read book The Combination of Biased and Robust Estimation Techniques in Multiple Regression Models written by Ronald Gene Askin and published by . This book was released on 1979 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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