Universal Coding and Order Identification by Model Selection Methods, ?lisabeth Gassiat
Автор: Wouter De Nooy, Andrej Mrvar, Vladimir Batagelj Название: Exploratory Social Network Analysis with Pajek. Revised and Expanded Edition for Updated Software ISBN: 1108462278 ISBN-13(EAN): 9781108462273 Издательство: Cambridge Academ Рейтинг: Цена: 43290.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The textbook on analysis and visualization of social networks that integrates theory, applications, and professional software for performing network analysis. Pajek software and datasets for all examples are freely available, so the reader can learn network analysis by doing it. Each chapter offers case studies for practicing network analysis.
Автор: Gassiat Название: Universal Coding and Order Identification by Model Selection Methods ISBN: 3319962612 ISBN-13(EAN): 9783319962610 Издательство: Springer Рейтинг: Цена: 102480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: 1.Lossless Coding.- 2.Universal Coding on Finite Alphabets.- 3.Universal Coding on Infinite Alphabets.- 4.Model Order Estimation.- Notation.- Index.
Автор: S?derstr?m Название: Errors-in-Variables Methods in System Identification ISBN: 3319750003 ISBN-13(EAN): 9783319750002 Издательство: Springer Рейтинг: Цена: 158380.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents an overview of the different errors-in-variables (EIV) methods that can be used for system identification.
Автор: Torsten S?derstr?m Название: Errors-in-Variables Methods in System Identification ISBN: 3030091252 ISBN-13(EAN): 9783030091255 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Поставка под заказ. Описание: This book presents an overview of the different errors-in-variables (EIV) methods that can be used for system identification. Readers will explore the properties of an EIV problem. Such problems play an important role when the purpose is the determination of the physical laws that describe the process, rather than the prediction or control of its future behaviour. EIV problems typically occur when the purpose of the modelling is to get physical insight into a process. Identifiability of the model parameters for EIV problems is a non-trivial issue, and sufficient conditions for identifiability are given. The author covers various modelling aspects which, taken together, can find a solution, including the characterization of noise properties, extension to multivariable systems, and continuous-time models. The book finds solutions that are constituted of methods that are compatible with a set of noisy data, which traditional approaches to solutions, such as (total) least squares, do not find. A number of identification methods for the EIV problem are presented. Each method is accompanied with a detailed analysis based on statistical theory, and the relationship between the different methods is explained. A multitude of methods are covered, including: instrumental variables methods; methods based on bias-compensation; covariance matching methods; and prediction error and maximum-likelihood methods. The book shows how many of the methods can be applied in either the time or the frequency domain and provides special methods adapted to the case of periodic excitation. It concludes with a chapter specifically devoted to practical aspects and user perspectives that will facilitate the transfer of the theoretical material to application in real systems. Errors-in-Variables Methods in System Identification gives readers the possibility of recovering true system dynamics from noisy measurements, while solving over-determined systems of equations, making it suitable for statisticians and mathematicians alike. The book also acts as a reference for researchers and computer engineers because of its detailed exploration of EIV problems.
Автор: ByoungSeon Choi Название: ARMA Model Identification ISBN: 1461397472 ISBN-13(EAN): 9781461397472 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The main topics covered include: Box-Jenkins` method, inverse autocorrelation functions, penalty function identification such as AIC, BIC techniques and Hannan and Quinn`s method, instrumental regression, and a range of pattern identification methods.
Автор: Izak Bos; Peter Caligari Название: Selection Methods in Plant Breeding ISBN: 9048176166 ISBN-13(EAN): 9789048176168 Издательство: Springer Рейтинг: Цена: 191550.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Written for plant breeders, researchers and post-graduate students, this excellent new book provides a comprehensive review of the methods and underlying theoretical foundations used for selection in plant breeding programs.
Автор: Antonio Aznar Grasa Название: Econometric Model Selection ISBN: 904814051X ISBN-13(EAN): 9789048140510 Издательство: Springer Рейтинг: Цена: 158380.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book proposes a new methodology for the selection of one (model) from among a set of alternative econometric models.
Автор: Luca Oneto Название: Model Selection and Error Estimation in a Nutshell ISBN: 3030243583 ISBN-13(EAN): 9783030243586 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Поставка под заказ. Описание: How can we select the best performing data-driven model? How can we rigorously estimate its generalization error? Statistical learning theory answers these questions by deriving non-asymptotic bounds on the generalization error of a model or, in other words, by upper bounding the true error of the learned model based just on quantities computed on the available data. However, for a long time, Statistical learning theory has been considered only an abstract theoretical framework, useful for inspiring new learning approaches, but with limited applicability to practical problems. The purpose of this book is to give an intelligible overview of the problems of model selection and error estimation, by focusing on the ideas behind the different statistical learning theory approaches and simplifying most of the technical aspects with the purpose of making them more accessible and usable in practice. The book starts by presenting the seminal works of the 80’s and includes the most recent results. It discusses open problems and outlines future directions for research.
Автор: Ando, Tomohiro Название: Bayesian Model Selection and Statistical Modeling ISBN: 0367383977 ISBN-13(EAN): 9780367383978 Издательство: Taylor&Francis Рейтинг: Цена: 65320.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Along with many practical applications, Bayesian Model Selection and Statistical Modeling presents an array of Bayesian inference and model selection procedures. It thoroughly explains the concepts, illustrates the derivations of various Bayesian model selection criteria through examples, and provides R code for implementation.
The author shows how to implement a variety of Bayesian inference using R and sampling methods, such as Markov chain Monte Carlo. He covers the different types of simulation-based Bayesian model selection criteria, including the numerical calculation of Bayes factors, the Bayesian predictive information criterion, and the deviance information criterion. He also provides a theoretical basis for the analysis of these criteria. In addition, the author discusses how Bayesian model averaging can simultaneously treat both model and parameter uncertainties.
Selecting and constructing the appropriate statistical model significantly affect the quality of results in decision making, forecasting, stochastic structure explorations, and other problems. Helping you choose the right Bayesian model, this book focuses on the framework for Bayesian model selection and includes practical examples of model selection criteria.
Автор: Wouter De Nooy, Andrej Mrvar, Vladimir Batagelj Название: Exploratory Social Network Analysis with Pajek: Revised and Expanded Edition for Updated Software ISBN: 1108474144 ISBN-13(EAN): 9781108474146 Издательство: Cambridge Academ Рейтинг: Цена: 121440.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The textbook on analysis and visualization of social networks that integrates theory, applications, and professional software for performing network analysis. Pajek software and datasets for all examples are freely available, so the reader can learn network analysis by doing it. Each chapter offers case studies for practicing network analysis.
Автор: Cattaneo, Matias D. (university Of Michigan, Ann Arbor) Idrobo, Nicolas (university Of Michigan, Ann Arbor) Titiunik, Rocio (university Of Michigan, A Название: Elements in quantitative and computational methods for the social sciences ISBN: 1108710204 ISBN-13(EAN): 9781108710206 Издательство: Cambridge Academ Рейтинг: Цена: 19010.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: An accessible and practical guide for the analysis and interpretation of regression discontinuity (RD) designs. The focus is on the canonical sharp RD setup that has the following features: (i) the score is continuously distributed and has only one dimension, (ii) there is only one cutoff, and (iii) compliance with the treatment assignment is perfect.
Автор: Jos W. R. Twisk Название: Applied Mixed Model Analysis: A Practical Guide ISBN: 1108480578 ISBN-13(EAN): 9781108480574 Издательство: Cambridge Academ Рейтинг: Цена: 111930.00 T Наличие на складе: Невозможна поставка. Описание: This book explains all aspects of mixed model analysis without mathematical jargon, so that non-statisticians can understand the basic principles, analyze their own data, and interpret the results with confidence. Worked examples are analyzed with STATA, and all datasets are available for download, equipping readers to replicate the methods.
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