Methodology In Robust And Nonparametric Statistics
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Methodology in Robust and Nonparametric Statistics
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
Robust Nonparametric Statistical Methods
Author: Thomas P. Hettmansperger
language: en
Publisher: Hodder Education
Release Date: 1998
Based in ranks of the data, this book offers an alternative to the traditional least squares approach. Topics include one- and two-sample location models, linear models (including multiple regression and designed experiments), and multivariate models. Rank tests and estimates for all models are developed, including bounded influence and high breakdown methods. Emphasis is on efficiency and robustness and all methods are illustrated on data sets.
Robust Nonparametric Statistical Methods
Author: Thomas P. Hettmansperger
language: en
Publisher: CRC Press
Release Date: 2010-12-20
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