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Bilinear Regression Analysis, von Rosen


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Цена: 10480.00р.
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Автор: von Rosen
Название:  Bilinear Regression Analysis
ISBN: 9783319787824
Издательство: Springer
Классификация:


ISBN-10: 3319787829
Обложка/Формат: Paperback
Вес: 0.67 кг.
Дата издания: 2018
Серия: Lecture Notes in Statistics
Язык: English
Издание: 1st ed. 2018
Иллюстрации: 42 illustrations, black and white; approx. 450 p. 42 illus.
Размер: 157 x 235 x 32
Читательская аудитория: General (us: trade)
Основная тема: Statistical Theory and Methods
Подзаголовок: An Introduction
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book expands on the classical statistical multivariate analysis theory by focusing on bilinear regression models, a class of models comprising the classical growth curve model and its extensions. In order to analyze the bilinear regression models in an interpretable way, concepts from linear models are extended and applied to tensor spaces. Further, the book considers decompositions of tensor products into natural subspaces, and addresses maximum likelihood estimation, residual analysis, influential observation analysis and testing hypotheses, where properties of estimators such as moments, asymptotic distributions or approximations of distributions are also studied. Throughout the text, examples and several analyzed data sets illustrate the different approaches, and fresh insights into classical multivariate analysis are provided. This monograph is of interest to researchers and Ph.D. students in mathematical statistics, signal processing and other fields where statistical multivariate analysis is utilized. It can also be used as a text for second graduate-level courses on multivariate analysis.
Дополнительное описание: Preface.- Introduction.- The Basic Ideas of Obtaining MLEs: A Known Dispersion.- The Basic Ideas of Obtaining MLEs: Unknown Dispersion.- Basic Properties of Estimators.- Density Approximations.- Residuals.- Testing Hypotheses.- Influential Observations.-



Bilinear Stochastic Models and Related Problems of Nonlinear Time Series Analysis

Автор: Gy?rgy Terdik
Название: Bilinear Stochastic Models and Related Problems of Nonlinear Time Series Analysis
ISBN: 0387988726 ISBN-13(EAN): 9780387988726
Издательство: Springer
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Цена: 14673.00 р.
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Описание: The first two chapters are devoted to the basic theory of nonlinear functions of stationary Gaussian processes, Hermite polynomials, cumulants and higher order spectra, multiple Wiener-Ito integrals and finally chaotic Wiener-Ito spectral representation of subordinated processes.

Design and Analysis of Experiments

Автор: Onyiah, Leonard C.
Название: Design and Analysis of Experiments
ISBN: 0367387077 ISBN-13(EAN): 9780367387075
Издательство: Taylor&Francis
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Цена: 9798.00 р.
Наличие на складе: Нет в наличии.

Описание:

Unlike other books on the modeling and analysis of experimental data, Design and Analysis of Experiments: Classical and Regression Approaches with SAS not only covers classical experimental design theory, it also explores regression approaches. Capitalizing on the availability of cutting-edge software, the author uses both manual methods and SAS programs to carry out analyses.

The book presents most of the different designs covered in a typical experimental design course. It discusses the requirements for good experimentation, the completely randomized design, the use of orthogonal contrast to test hypotheses, and the model adequacy check. With an emphasis on two-factor factorial experiments, the author analyzes repeated measures as well as fixed, random, and mixed effects models. He also describes designs with randomization restrictions, before delving into the special cases of the 2k and 3k factorial designs, including fractional replication and confounding. In addition, the book covers response surfaces, balanced incomplete block and hierarchical designs, ANOVA, ANCOVA, and MANOVA.

Fortifying the theory and computations with practical exercises and supplemental material, this distinctive text provides a modern, comprehensive treatment of experimental design and analysis.

An Introduction to Bispectral Analysis and Bilinear Time Series Models

Автор: T.S. Rao; M.M. Gabr
Название: An Introduction to Bispectral Analysis and Bilinear Time Series Models
ISBN: 0387960392 ISBN-13(EAN): 9780387960395
Издательство: Springer
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Цена: 16769.00 р.
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Описание: The theory of time series models has been well developed over the last thirt,y years. The most interesting feature of such a model is that its second order covariance analysis is ve~ similar to that for a linear model. This demonstrates the importance of higher order covariance analysis for nonlinear models.

Bilinear Forms and Zonal Polynomials

Автор: Arak M. Mathai; Serge B. Provost; Takesi Hayakawa
Название: Bilinear Forms and Zonal Polynomials
ISBN: 0387945229 ISBN-13(EAN): 9780387945224
Издательство: Springer
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Цена: 15372.00 р.
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Описание: Deals with bilinear forms in real random vectors and their generalizations. This monograph shows how zonal polynomials may be used to analyze such forms and thus to apply these concepts in a variety of statistical settings.

Bilinear Algebra

Автор: Szymiczek, Kazimierz
Название: Bilinear Algebra
ISBN: 9056990764 ISBN-13(EAN): 9789056990763
Издательство: Taylor&Francis
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Цена: 29093.00 р.
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Bilinear Control Systems

Автор: David Elliott
Название: Bilinear Control Systems
ISBN: 9048181690 ISBN-13(EAN): 9789048181698
Издательство: Springer
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Цена: 12157.00 р.
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Описание: The mathematical theory of control became a ?eld of study half a century ago in attempts to clarify and organize some challenging practical problems and the methods used to solve them. It is known for the breadth of the mathematics it uses and its cross-disciplinary vigor. Its literature, which can befoundinSection93ofMathematicalReviews, wasatonetimedominatedby the theory of linear control systems, which mathematically are described by linear di?erential equations forced by additive control inputs. That theory led to well-regarded numerical and symbolic computational packages for control analysis and design. Nonlinear control problems are also important; in these either the - derlying dynamical system is nonlinear or the controls are applied in a n- additiveway.Thelastfourdecadeshaveseenthedevelopmentoftheoretical work on nonlinear control problems based on di?erential manifold theory, nonlinear analysis, and several other mathematical disciplines. Many of the problems that had been solved in linear control theory, plus others that are new and distinctly nonlinear, have been addressed; some resulting general de?nitions and theorems are adapted in this book to the bilinear case

Advanced Statistics for Testing Assumed Causal Relationships

Автор: Hooshang Nayebi
Название: Advanced Statistics for Testing Assumed Causal Relationships
ISBN: 3030547531 ISBN-13(EAN): 9783030547530
Издательство: Springer
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Цена: 11179.00 р.
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Описание: It presents that potential effects of each independent variable on the dependent variable are not limited to direct and indirect effects. The path analysis shows each independent variable has a pure effect on the dependent variable. So, it can be shown the unique contribution of each independent variable to the variation of the dependent variable.

Understanding Regression Analysis: An Introductory Guide

Автор: Schroeder Larry D., Sjoquist David L., Stephan Pau
Название: Understanding Regression Analysis: An Introductory Guide
ISBN: 1506332889 ISBN-13(EAN): 9781506332888
Издательство: Sage Publications
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Цена: 5859.00 р.
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Описание: Presents the fundamentals of regression analysis, from its meaning to uses, in a concise, easy-to-read, and non-technical style.

Understanding Regression Analysis

Автор: Westfall, Peter , Arias, Andrea L.
Название: Understanding Regression Analysis
ISBN: 0367493519 ISBN-13(EAN): 9780367493516
Издательство: Taylor&Francis
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Цена: 6583.00 р.
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Описание: This book unifies diverse regression applications including the classical model, ANOVA models, generalized models including Poisson, Negative binomial, logistic, and survival, neural networks and decision trees under a common umbrella; namely, the conditional distribution model.

Theory of Ridge Regression Estimators with Applica tions

Автор: Saleh
Название: Theory of Ridge Regression Estimators with Applica tions
ISBN: 1118644611 ISBN-13(EAN): 9781118644614
Издательство: Wiley
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Цена: 16466.00 р.
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Описание:

This book discusses current methods of estimation in linearmodels. In particular, the authors address the methodology oflinear multiple regression models that plays an important role inalmost every scientific investigations in various fields, including economics, engineering, and biostatistics. Thestandard estimation method for regression parameters is theordinary least square (OLS) principal where residual squared errorsare minimized. Applied statisticians are often not satisfied withOLS estimators when the design matrix is ill-conditioned, leadingto a multicollinearity problem and large variances that make the"prediction" inaccurate. This book details theridge regression estimator, which was developed to combat themulticollinearity problem. Another estimator, called theLiu-estimator due to Liu Kejian, is also addressed since itprovides a competing resolution to the multicollinearityproblem. The ridge regression estimators are complicatednon-linear functions of the ridge parameter, whereas, theLiu estimators are a linear function of the shrinkage parameter.With a focus on the ridge regression and LIU estimators, this bookprovides expanded coverage beyond the usual preliminary test andStein type estimator. In this case, we propose a class of compositeestimators that are obtained by multiplying the OLS, restrictedOLS, preliminary test OLS, and Stein-type OLS by the "ridgefactor" and "Liu-factor." This research is asignificant step towards the study of dominance properties as wellas the comparison of the extent of LASSO properties. In addition, research materials involving shrinkage and model selection forlinear regression models are provided. Topical coverageincludes: preliminaries; linear regression models; multipleregression models; measurement error models; generalized linearmodels; and autoregressive Gaussian processes.

Linear Models And Regression With R: An Integrated Approach

Автор: Jammalamadaka S Rao, Sengupta Debasis
Название: Linear Models And Regression With R: An Integrated Approach
ISBN: 9811200408 ISBN-13(EAN): 9789811200403
Издательство: World Scientific Publishing
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Цена: от 6763.00 р.
Наличие на складе: Есть

Описание:

Starting with the basic linear model where the design and covariance matrices are of full rank, this book demonstrates how the same statistical ideas can be used to explore the more general linear model with rank-deficient design and/or covariance matrices. The unified treatment presented here provides a clearer understanding of the general linear model from a statistical perspective, thus avoiding the complex matrix-algebraic arguments that are often used in the rank-deficient case. Elegant geometric arguments are used as needed.

The book has a very broad coverage, from illustrative practical examples in Regression and Analysis of Variance alongside their implementation using R, to providing comprehensive theory of the general linear model with 181 worked-out examples, 227 exercises with solutions, 152 exercises without solutions (so that they may be used as assignments in a course), and 320 up-to-date references.

This completely updated and new edition of Linear Models: An Integrated Approach includes the following features:

  • Applications with data sets, and their implementation in R,
  • Comprehensive coverage of regression diagnostics and model building,
  • Coverage of other special topics such as collinearity, stochastic and inequality constraints, misspecified models, etc.,
  • Use of simple statistical ideas and interpretations to explain advanced concepts, and simpler proofs of many known results,
  • Discussion of models covering mixed-effects/variance components, spatial, and time series data with partially unknown dispersion matrix,
  • Thorough treatment of the singular linear model, including the case of multivariate response,
  • Insight into updates in the linear model, and their connection with diagnostics, design, variable selection, Kalman filter, etc.,
  • Extensive discussion of the foundations of linear inference, along with linear alternatives to least squares.
Meta-Regression Analysis in Economics and Business

Автор: Stanley, T.D.
Название: Meta-Regression Analysis in Economics and Business
ISBN: 0415670780 ISBN-13(EAN): 9780415670784
Издательство: Taylor&Francis
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Цена: 23734.00 р.
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