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hannu oja robust correlation theory and applications

Hannu Oja Robust Correlation. Theory and Applications hannu oja robust correlation theory and applications

Hannu Oja Robust Cor...

This bookpresents material on both the analysis of the classical conce...

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Цена: 7289.78 RUR

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Kang-Zhi Liu Robust Control. Theory and Applications hannu oja robust correlation theory and applications

Kang-Zhi Liu Robust...

Comprehensive and up to date coverage of robust control theory and its...

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Цена: 13134.85 RUR

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Ricardo Maronna A. Robust Statistics. Theory and Methods (with R) hannu oja robust correlation theory and applications

Ricardo Maronna A. R...

A new edition of this popular text on robust statistics, thoroughly up...

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Цена: 11340.84 RUR

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Brenton Clarke R. Robustness Theory and Application hannu oja robust correlation theory and applications

Brenton Clarke R. Ro...

A preeminent expert in the field explores new and exciting methodologi...

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Behrouz Farhang-Boroujeny Adaptive Filters. Theory and Applications hannu oja robust correlation theory and applications

Behrouz Farhang-Boro...

This second edition of Adaptive Filters: Theory and Applications has b...

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Цена: 11410.54 RUR

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He Matthew Mathematics of Bioinformatics. Theory, Methods and Applications hannu oja robust correlation theory and applications

He Matthew Mathemati...

Mathematics of Bioinformatics: Theory, Methods, and Applications provi...

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Aliakbar Haghighi Montazer Difference and Differential Equations with Applications in Queueing Theory hannu oja robust correlation theory and applications

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A Useful Guide to the Interrelated Areas of Differential Equations, Di...

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Цена: 10097.44 RUR

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Peter Carr Advanced Equity Derivatives. Volatility and Correlation hannu oja robust correlation theory and applications

Peter Carr Advanced...

In Advanced Equity Derivatives: Volatility and Correlation, Sébastien...

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Цена: 11492.31 RUR

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Ronald Pethig R. Dielectrophoresis. Theory, Methodology and Biological Applications hannu oja robust correlation theory and applications

Ronald Pethig R. Die...

Comprehensive coverage of the basic theoretical concepts and applicati...

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Vijay Garg K. Introduction to Lattice Theory with Computer Science Applications hannu oja robust correlation theory and applications

Vijay Garg K. Introd...

A computational perspective on partial order and lattice theory, focus...

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Цена: 7798.35 RUR

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Zhong-Ping Jiang Robust Adaptive Dynamic Programming hannu oja robust correlation theory and applications

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A comprehensive look at state-of-the-art ADP theory and real-world app...

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Ali Akansu N. Financial Signal Processing and Machine Learning hannu oja robust correlation theory and applications

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The modern financial industry has been required to deal with large and...

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Clement Kleinstreuer Microfluidics and Nanofluidics. Theory and Selected Applications hannu oja robust correlation theory and applications

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Fluidics originated as the description of pneumatic and hydraulic cont...

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Xianlin Han Lipidomics. Comprehensive Mass Spectrometry of Lipids hannu oja robust correlation theory and applications

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Covers the area of lipidomics from fundamentals and theory to applicat...

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Łukasz Dawidowski Scales of Banach Spaces, Theory of Interpolation and their Applications hannu oja robust correlation theory and applications

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Łukasz Dawidowski Scales of Banach Spaces, Theory of Interpolation and...

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Michael O'Leary L. A First Course in Mathematical Logic and Set Theory hannu oja robust correlation theory and applications

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A mathematical introduction to the theory and applications of logic an...

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Для информации:

A new edition of this popular text on robust statistics, thoroughly updated to include new and improved methods and focus on implementation of methodology using the increasingly popular open-source software R. Classical statistics fail to cope well with outliers associated with deviations from standard distributions. Robust statistical methods take into account these deviations when estimating the parameters of parametric models, thus increasing the reliability of fitted models and associated inference. This new, second edition of Robust Statistics: Theory and Methods (with R) presents a broad coverage of the theory of robust statistics that is integrated with computing methods and applications. Updated to include important new research results of the last decade and focus on the use of the popular software package R, it features in-depth coverage of the key methodology, including regression, multivariate analysis, and time series modeling. The book is illustrated throughout by a range of examples and applications that are supported by a companion website featuring data sets and R code that allow the reader to reproduce the examples given in the book. Unlike other books on the market, Robust Statistics: Theory and Methods (with R) offers the most comprehensive, definitive, and up-to-date treatment of the subject. It features chapters on estimating location and scale; measuring robustness; linear regression with fixed and with random predictors; multivariate analysis; generalized linear models; time series; numerical algorithms; and asymptotic theory of M-estimates. Explains both the use and theoretical justification of robust methods Guides readers in selecting and using the most appropriate robust methods for their problems Features computational algorithms for the core methods Robust statistics research results of the last decade included in this 2nd edition include: fast deterministic robust regression, finite-sample robustness, robust regularized regression, robust location and scatter estimation with missing data, robust estimation with independent outliers in variables, and robust mixed linear models. Robust Statistics aims to stimulate the use of robust methods as a powerful tool to increase the reliability and accuracy of statistical modelling and data analysis. It is an ideal resource for researchers, practitioners, and graduate students in statistics, engineering, computer science, and physical and social sciences.