Robust Nonlinear Regression | With Applications Using R. Este artículo no está disponible.
Idioma: inglés
Editorial: Wiley, 2018
- Tapa dura
- Nuevo
Librería: preigu, Osnabrück, Alemaniapreigu
Vendedor de IberLibro desde 5 de agosto de 2024
Condición: Nuevo
EUR 119,15
Descripción del artículo del vendedor
Robust Nonlinear Regression | With Applications Using R | Hossein Riazoshams (u. a.) | Buch | Preface xiAcknowledgements xiiiAbout the Companion Website xvPart One Theories 11 Robust Statistics and its Application in Linear Regression 31.1 Robust Aspects of Data 31.2 Robust Statistics and the Mechanism for Producing Outliers 41.3 Location and Sca | Englisch | 2018 | Wiley | EAN 9781118738061 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
N° de ref. del artículo 110510376
- Título
- Robust Nonlinear Regression | With Applications Using R
- Autor
- Hossein Riazoshams (u. a.)
- Editorial
- Wiley
- Año de publicación
- 2018
- Estado
- Neu
- Encuadernación
- Buch
- Idioma
- inglés
- ISBN 10
- 1118738063
- ISBN 13
- 9781118738061
- Peso del artículo
- 457 gramos
- Dimensiones
- 238 x 159 x 19 mm
- Catálogos de vendedores
- Bücher
The first book to discuss robust aspects of nonlinear regression―with applications using R software
Robust Nonlinear Regression: with Applications using R covers a variety of theories and applications of nonlinear robust regression. It discusses both parts of the classic and robust aspects of nonlinear regression and focuses on outlier effects. It develops new methods in robust nonlinear regression and implements a set of objects and functions in S-language under SPLUS and R software. The software covers a wide range of robust nonlinear fitting and inferences, and is designed to provide facilities for computer users to define their own nonlinear models as an object, and fit models using classic and robust methods as well as detect outliers. The implemented objects and functions can be applied by practitioners as well as researchers.
The book offers comprehensive coverage of the subject in 9 chapters: Theories of Nonlinear Regression and Inference; Introduction to R; Optimization; Theories of Robust Nonlinear Methods; Robust and Classical Nonlinear Regression with Autocorrelated and Heteroscedastic errors; Outlier Detection; R Packages in Nonlinear Regression; A New R Package in Robust Nonlinear Regression; and Object Sets.
- The first comprehensive coverage of this field covers a variety of both theoretical and applied topics surrounding robust nonlinear regression
- Addresses some commonly mishandled aspects of modeling
- R packages for both classical and robust nonlinear regression are presented in detail in the book and on an accompanying website
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Acerca del autor
Hossein Riazoshams, PhD, is a full-time Faculty member at the Department of Mathematics and Statistics, Lamerd Islamic Azad University of Iran; Stockholm University, Sweden; and University of Putra, Malaysia.
Habshah Midi, PhD, is Professor at the Department of Mathematics, Faculty of Science and Institute for Mathematical Research, University of Putra, Malaysia.
Gebrenegus Ghilagaber, PhD, is Professor and Head at the Department of Statistics, Stockholm University, Sweden.
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