Robust Methods for Data Reduction - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Robust Methods for Data Reduction write by Alessio Farcomeni. This book was released on 2016-01-13. Robust Methods for Data Reduction available in PDF, EPUB and Kindle. Robust Methods for Data Reduction gives a non-technical overview of robust data reduction techniques, encouraging the use of these important and useful methods in practical applications. The main areas covered include principal components analysis, sparse principal component analysis, canonical correlation analysis, factor analysis, clustering, dou
Application of Robust Statistical Methods to Data Reduction
Application of Robust Statistical Methods to Data Reduction - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Application of Robust Statistical Methods to Data Reduction write by William S. Agee. This book was released on 1978. Application of Robust Statistical Methods to Data Reduction available in PDF, EPUB and Kindle. Robust Statistics provides a fresh approach to the difficult problem of editing in data reduction. Of prime concern are grossly erroneous measurements which, when undetected, completely destroy automated data reduction procedures causing costly reruns and time delays with human detection of the erroneous measurements. The application of robust statistical methods has been highly successful in dealing with this problem. An introduction to the robust M-estimates and their numerical computation is given. The application of M-estimates to data preprocessing, instrument calibration, N-station cinetheodolites, N-station radar solution, and filtering are described in detail. Numerical examples of these applications using real measurements are given. (Author).
Robustness in Data Analysis
Robustness in Data Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Robustness in Data Analysis write by Georgij Leonidovič Ševljakov. This book was released on 2002. Robustness in Data Analysis available in PDF, EPUB and Kindle. The field of mathematical statistics called robustness statistics deals with the stability of statistical inference under variations of accepted distribution models. Although robust statistics involves mathematically highly defined tools, robust methods exhibit a satisfactory behaviour in small samples, thus being quite useful in applications. This volume in the book series Modern Probability and Statistics addresses various topics in the field of robust statistics and data analysis, such as: a probability-free approach in data analysis; minimax variance estimators of location, scale, regression, autoregression and correlation; "L1-norm methods; adaptive, data reduction, bivariate boxplot, and multivariate outlier detection algorithms; applications in reliability, detection of signals, and analysis of the sudden cardiac death risk factors. The book contains new results related to robustness and data analysis technologies, including both theoretical aspects and practical needs of data processing, which have been relatively inaccessible as they were originally only published in Russian. This book will be of value and interest to researchers in mathematical statistics as well as to those using statistical methods.
Soft Methods for Data Science
Soft Methods for Data Science - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Soft Methods for Data Science write by Maria Brigida Ferraro. This book was released on 2016-08-30. Soft Methods for Data Science available in PDF, EPUB and Kindle. This proceedings volume is a collection of peer reviewed papers presented at the 8th International Conference on Soft Methods in Probability and Statistics (SMPS 2016) held in Rome (Italy). The book is dedicated to Data science which aims at developing automated methods to analyze massive amounts of data and to extract knowledge from them. It shows how Data science employs various programming techniques and methods of data wrangling, data visualization, machine learning, probability and statistics. The soft methods proposed in this volume represent a collection of tools in these fields that can also be useful for data science.
Robust Multivariate Analysis
Robust Multivariate Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Robust Multivariate Analysis write by David J. Olive. This book was released on 2017-11-28. Robust Multivariate Analysis available in PDF, EPUB and Kindle. This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain types of outliers. Instead of using exact theory based on the multivariate normal distribution, the simpler and more applicable large sample theory is given. The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed by theory. The robust techniques are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis. A simple way to bootstrap confidence regions is also provided. Much of the research on robust multivariate analysis in this book is being published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics. This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with outliers. Many R programs and R data sets are available on the author’s website.
