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Robust Estimation Based On Grouped Adjusted Data In Linear Regression Models
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Book Synopsis Robust Estimation Based on Grouped-adjusted Data in Linear Regression Models by : Stanford University. Econometric Workshop
Download or read book Robust Estimation Based on Grouped-adjusted Data in Linear Regression Models written by Stanford University. Econometric Workshop and published by . This book was released on 1985 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Estimation Based on Grouped-adjusted Data in Censored Regression Models by : Stanford University. Econometric Workshop
Download or read book Robust Estimation Based on Grouped-adjusted Data in Censored Regression Models written by Stanford University. Econometric Workshop and published by . This book was released on 1986 with total page 61 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Estimation Based on Grouped-adjusted Data by : Kazumitsu Nawata
Download or read book Robust Estimation Based on Grouped-adjusted Data written by Kazumitsu Nawata and published by . This book was released on 1986 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 On Efficient and Robust Estimation in Semiparametric Linear Regression Models with Missing Data by : Alex Catane Bajamonde
Download or read book On Efficient and Robust Estimation in Semiparametric Linear Regression Models with Missing Data written by Alex Catane Bajamonde and published by . This book was released on 1991 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Estimation of Generalized Regression Models by the Grouping Method by : Kazumitsu Nawata
Download or read book Estimation of Generalized Regression Models by the Grouping Method written by Kazumitsu Nawata and published by . This book was released on 1993 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Distributionally Robust Learning by : Ruidi Chen
Download or read book Distributionally Robust Learning written by Ruidi Chen and published by . This book was released on 2020-12-23 with total page 258 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 JOURNAL OF ECONOMETRICS: ANNALS 1991-3, THE MEASUREMENT AND ANALYSIS OF WELFARE -- VOLUME 50 (1991) by :
Download or read book JOURNAL OF ECONOMETRICS: ANNALS 1991-3, THE MEASUREMENT AND ANALYSIS OF WELFARE -- VOLUME 50 (1991) written by and published by . This book was released on 1991 with total page 824 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Modern Statistics with R by : Måns Thulin
Download or read book Modern Statistics with R written by Måns Thulin and published by CRC Press. This book was released on 2024-08-20 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. Modern Statistics with R introduces you to key parts of this modern statistical toolkit. It teaches you: Data wrangling - importing, formatting, reshaping, merging, and filtering data in R. Exploratory data analysis - using visualisations and multivariate techniques to explore datasets. Statistical inference - modern methods for testing hypotheses and computing confidence intervals. Predictive modelling - regression models and machine learning methods for prediction, classification, and forecasting. Simulation - using simulation techniques for sample size computations and evaluations of statistical methods. Ethics in statistics - ethical issues and good statistical practice. R programming - writing code that is fast, readable, and (hopefully!) free from bugs. No prior programming experience is necessary. Clear explanations and examples are provided to accommodate readers at all levels of familiarity with statistical principles and coding practices. A basic understanding of probability theory can enhance comprehension of certain concepts discussed within this book. In addition to plenty of examples, the book includes more than 200 exercises, with fully worked solutions available at: www.modernstatisticswithr.com.
Book Synopsis Österreichisches UNIX Forum ; 5 by :
Download or read book Österreichisches UNIX Forum ; 5 written by and published by . This book was released on 1990 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Estimation in Nonlinear Regression and Limited Dependent Variable Models by : Pavel Čížek
Download or read book Robust Estimation in Nonlinear Regression and Limited Dependent Variable Models written by Pavel Čížek and published by . This book was released on 2001 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Estimation in Structured Linear Regression by : Lamine Mili
Download or read book Robust Estimation in Structured Linear Regression written by Lamine Mili and published by . This book was released on 1993 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistical Theory and Method Abstracts by :
Download or read book Statistical Theory and Method Abstracts written by and published by . This book was released on 1992 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Adaptive Regression by : Yadolah Dodge
Download or read book Adaptive Regression written by Yadolah Dodge and published by Springer Science & Business Media. This book was released on 2012-10-01 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: While there have been a large number of estimation methods proposed and developed for linear regression, none has proved good for all purposes. This text focuses on the construction of an adaptive combination of two estimation methods so as to help users make an objective choice and combine the desirable properties of two estimators.
Book Synopsis Robust Estimation of the Number of Components for Mixtures of Linear Regression by : Li Meng
Download or read book Robust Estimation of the Number of Components for Mixtures of Linear Regression written by Li Meng and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this report, we investigate a robust estimation of the number of components in the mixture of regression models using trimmed information criterion. Compared to the traditional information criterion, the trimmed criterion is robust and not sensitive to outliers. The superiority of the trimmed methods in comparison with the traditional information criterion methods is illustrated through a simulation study. A real data application is also used to illustrate the effectiveness of the trimmed model selection methods.
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.
