Todorov valentin (8 resultados)
Robust Statistics Through the Monitoring Approach: Applications in Regression (Springer Series in Statistics)
Atkinson, Anthony C.; Riani, Marco; Corbellini, Aldo; Perrotta, Domenico; Todorov, Valentin
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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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EUR 65,79
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Condición: New.
Robust Statistics Through the Monitoring Approach: Applications in Regression
Atkinson, Anthony C./ Riani, Marco/ Corbellini, Aldo/ Perrotta, Domenico/ Todorov, Valentin
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 91,54
Envío por EUR 14,55Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Hardcover. Condición: Brand New. 573 pages. 9.26x6.11x9.21 inches. In Stock.
Idioma: Inglés
Editorial: Südwestdeutscher Verlag für Hochschulschriften, 2015
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Librería: preigu, Osnabrück, Alemaniapreigu
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EUR 69,90
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Taschenbuch. Condición: Neu. Multivariate Robust Statistics | Methods and Computation | Valentin Todorov (u. a.) | Taschenbuch | 156 S. | Deutsch | 2015 | Südwestdeutscher Verlag für Hochschulschriften | EAN 9783838108148 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at…]preigu[dot]de | Anbieter: preigu.
Robust Statistics Through the Monitoring Approach
Anthony C. Atkinson, Marco Riani, Aldo Corbellini, Domenico Perrotta, Valentin Todorov
- Tapa dura
Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK
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EUR 73,55
Envío por EUR 75,65Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Hardback. Condición: New. This open access book presents robust statistical methods and procedures through the monitoring approach, with an emphasis on applications to linear regression. Illustrating the theory, it explores both large and small-sample properties. The performance of the forward search and of the monitoring of sta…tic robust estimators for regression data are illuminated through numerous data analyses using MATLAB and R.The book describes the results of many years' work of the authors in the development of powerful methods of robust regression analysis. Robust methods are designed to analyse contaminated data. The well-established static robust methods estimate model features, such as parameter estimates, assuming the amount of contamination in the data is known. These methods are described in detail in Chapter 2 for estimation in a simple sample. The extension to regression is presented in Chapter 3, with an emphasis on S-estimation and related procedures as well as on least trimmed squares. The monitoring methods of Chapter 4, including the forward search, find the appropriate level of robustness for each data set and so avoid biased estimation from the inclusion of outliers and inefficiency due to the deletion of uncontaminated observations. This analysis is followed by examples which illustrate the use of the interactive graphical analyses associated with the authors' FSDA toolbox. Numerical comparisons of the size and power of outlier tests appear in Chapter 5. Later chapters illustrate applications to response transformation in regression and to non-parametric regression. Extensions of the robust multiple regression model include Bayesian, heteroskedastic, time series and compositional regression, together with the clustering of regression models. Finally, several approaches to model selection are investigated and robust analyses of regression data are presented that illustrate the use of the techniques introduced earlier. Exercises are given at the end of each chapter, with solutions at the end of the book. The MATLAB code can be reproduced using MATLAB Online, without the need for a license, or via the language-agnostic Jupyter notebook environment, after installing the MATLAB kernel. Online computer code is available for all examples and exercises, together with a series of YouTube videos.Aimed at professional statisticians and researchers concerned with insightful data analysis, as well as postgraduate students, the book may also serve as a text for a modern interactive robust regression course.
Robust Statistics Through the Monitoring Approach
Atkinson, Anthony C.; Riani, Marco; Corbellini, Aldo; Perrotta, Domenico; Todorov, Valentin
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Librería: moluna, Greven, Alemaniamoluna
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EUR 39,60
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.
Idioma: Inglés
Editorial: Südwestdeutscher Verlag Für Hochschulschriften AG Co. KG Sep 2015, 2015
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 69,90
Envío por EUR 23,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The goal of robust statistics is to develop methods that can cope with the presence of outliers in the data and nevertheless produce reasonable results. In this book some of the most popular robust multivariate methods are investiga…ted and new methods are proposed. Their performance is evaluated and compared in a variety of situations. The focus is on high breakdown point methods for discriminant analysis, multivariate tests and their basis, the robust estimators for multivariate location and covariance. The routine use of robust methods in a wide area of application domains is unthinkable without the computational power of today's personal computers and the availability of ready to use implementations of the algorithms. A unified computational platform organized as common patterns which we call statistical design patterns in analogy to the design patterns widely used in software engineering is proposed. The concrete implementation is an object oriented framework for robust multivariate analysis developed in R, an environment for statistical computing and graphics (R Development Core Team, 2009). 156 pp. Deutsch.
Idioma: Inglés
Editorial: Südwestdeutscher Verlag Für Hochschulschriften Jun 2009, 2009
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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EUR 69,90
Envío por EUR 60,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The goal of robust statistics is to develop methods that can cope with the presence of outliers in the data and nevertheless produce reasonable results. In this book some of the most popular robust multivariate methods are investigated…and new methods are proposed. Their performance is evaluated and compared in a variety of situations. The focus is on high breakdown point methods for discriminant analysis, multivariate tests and their basis, the robust estimators for multivariate location and covariance. The routine use of robust methods in a wide area of application domains is unthinkable without the computational power of today¿s personal computers and the availability of ready to use implementations of the algorithms. A unified computational platform organized as common patterns which we call statistical design patterns in analogy to the design patterns widely used in software engineering is proposed. The concrete implementation is an object oriented framework for robust multivariate analysis developed in R, an environment for statistical computing and graphics (R Development Core Team, 2009).VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 156 pp. Deutsch.
Idioma: Inglés
Editorial: Südwestdeutscher Verlag Für Hochschulschriften, 2009
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- Impresión bajo demanda
Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 69,90
Envío por EUR 61,25Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The goal of robust statistics is to develop methods that can cope with the presence of outliers in the data and nevertheless produce reasonable results. In this book some of the most popular robust multivariate methods are investigated a…nd new methods are proposed. Their performance is evaluated and compared in a variety of situations. The focus is on high breakdown point methods for discriminant analysis, multivariate tests and their basis, the robust estimators for multivariate location and covariance. The routine use of robust methods in a wide area of application domains is unthinkable without the computational power of today's personal computers and the availability of ready to use implementations of the algorithms. A unified computational platform organized as common patterns which we call statistical design patterns in analogy to the design patterns widely used in software engineering is proposed. The concrete implementation is an object oriented framework for robust multivariate analysis developed in R, an environment for statistical computing and graphics (R Development Core Team, 2009).
