Author: Ken-ichi YoshiharaPublisher:
ISBN:
Category : Sequences (Mathematics).
Languages : en
Pages : 356
Book Description
Weakly Dependent Stochastic Sequences and Their Applications: Curve estimation based on weakly dependent data
Author: Ken-ichi YoshiharaPublisher:
ISBN:
Category : Sequences (Mathematics).
Languages : en
Pages : 356
Book Description
Weakly Dependent Stochastic Sequences and Their Applications: Statistical inference based on weakly dependent data
Author: Ken-ichi YoshiharaPublisher:
ISBN:
Category : Sequences (Mathematics).
Languages : en
Pages : 408
Book Description
Weakly Dependent Stochastic Sequences and Their Applications: Generalized partial-sum processes
Author: Ken-ichi YoshiharaPublisher:
ISBN:
Category : Sequences (Mathematics).
Languages : en
Pages : 410
Book Description
Weakly Dependent Stochastic Sequences and Their Applications
Author: Ken-ichi YoshiharaPublisher:
ISBN:
Category : Sequences (Mathematics).
Languages : en
Pages : 378
Book Description
Nonparametric Functional Data Analysis
Author: Frédéric FerratyPublisher: Springer Science & Business Media
ISBN: 0387366202
Category : Mathematics
Languages : en
Pages : 260
Book Description
Modern apparatuses allow us to collect samples of functional data, mainly curves but also images. On the other hand, nonparametric statistics produces useful tools for standard data exploration. This book links these two fields of modern statistics by explaining how functional data can be studied through parameter-free statistical ideas. At the same time it shows how functional data can be studied through parameter-free statistical ideas, and offers an original presentation of new nonparametric statistical methods for functional data analysis.
Modeling Uncertainty
Author: Moshe DrorPublisher: Springer
ISBN: 0306481022
Category : Mathematics
Languages : en
Pages : 782
Book Description
Modeling Uncertainty: An Examination of Stochastic Theory, Methods, and Applications, is a volume undertaken by the friends and colleagues of Sid Yakowitz in his honor. Fifty internationally known scholars have collectively contributed 30 papers on modeling uncertainty to this volume. Each of these papers was carefully reviewed and in the majority of cases the original submission was revised before being accepted for publication in the book. The papers cover a great variety of topics in probability, statistics, economics, stochastic optimization, control theory, regression analysis, simulation, stochastic programming, Markov decision process, application in the HIV context, and others. There are papers with a theoretical emphasis and others that focus on applications. A number of papers survey the work in a particular area and in a few papers the authors present their personal view of a topic. It is a book with a considerable number of expository articles, which are accessible to a nonexpert - a graduate student in mathematics, statistics, engineering, and economics departments, or just anyone with some mathematical background who is interested in a preliminary exposition of a particular topic. Many of the papers present the state of the art of a specific area or represent original contributions which advance the present state of knowledge. In sum, it is a book of considerable interest to a broad range of academic researchers and students of stochastic systems.
Smoothing and Regression
Author: Michael G. SchimekPublisher: John Wiley & Sons
ISBN: 1118763300
Category : Mathematics
Languages : en
Pages : 682
Book Description
A comprehensive introduction to a wide variety of univariate and multivariate smoothing techniques for regression Smoothing and Regression: Approaches, Computation, and Application bridges the many gaps that exist among competing univariate and multivariate smoothing techniques. It introduces, describes, and in some cases compares a large number of the latest and most advanced techniques for regression modeling. Unlike many other volumes on this topic, which are highly technical and specialized, this book discusses all methods in light of both computational efficiency and their applicability for real data analysis. Using examples of applications from the biosciences, environmental sciences, engineering, and economics, as well as medical research and marketing, this volume addresses the theory, computation, and application of each approach. A number of the techniques discussed, such as smoothing under shape restrictions or of dependent data, are presented for the first time in book form. Special features of this book include: * Comprehensive coverage of smoothing and regression with software hints and applications from a wide variety of disciplines * A unified, easy-to-follow format * Contributions from more than 25 leading researchers from around the world * More than 150 illustrations also covering new graphical techniques important for exploratory data analysis and visualization of high-dimensional problems * Extensive end-of-chapter references For professionals and aspiring professionals in statistics, applied mathematics, computer science, and econometrics, as well as for researchers in the applied and social sciences, Smoothing and Regression is a unique and important new resource destined to become one the most frequently consulted references in the field.
Mathematical Reviews
Author: Bulletin of the Faculty of Engineering, Yokohama National University
Author: Dynamic Systems and Applications
Author: Publisher:
ISBN:
Category : Differentiable dynamical systems
Languages : en
Pages : 706
Book Description