Time-Like Graphical Models, Tvrtko Tadic

Автор: Roverato Alberto
Название: Graphical Models for Categorical Data
ISBN: 1108404960 ISBN-13(EAN): 9781108404969
Издательство: Cambridge Academ
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Цена: 31670.00 T
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Описание: For advanced students of network data science, this compact account covers both well-established methodology and the theory of models recently introduced in the graphical model literature. It focuses on the discrete case where all variables involved are categorical and, in this context, it achieves a unified presentation of classical and recent results.

Автор: Heidi H. Andersen; Malene Hojbjerre; Dorte Sorense
Название: Linear and Graphical Models
ISBN: 0387945210 ISBN-13(EAN): 9780387945217
Издательство: Springer
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Цена: 121110.00 T
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Описание: Provides an account of graphical models for multivariate complex normal distributions. Beginning with an introduction to the multivariate complex normal distribution, the authors develop the marginal and conditional distributions of random vectors and matrices. Then they introduce complex MANOVA models and hypothesis testing for these models.

Автор: M.I. Jordan
Название: Learning in Graphical Models
ISBN: 9401061041 ISBN-13(EAN): 9789401061049
Издательство: Springer
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Цена: 279500.00 T
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Описание: Proceedings of the NATO Advanced Study Institute, Ettore Maiorana Centre, Erice, Italy, September 27-October 7, 1996

Автор: Sucar, Luis Enrique
Название: Probabilistic graphical models
ISBN: 3030619427 ISBN-13(EAN): 9783030619428
Издательство: Springer
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Цена: 46570.00 T
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Описание:

This accessible text/reference provides a general introduction to probabilistic graphical models (PGMs) from an engineering perspective.

The book covers the fundamentals for each of the main classes of PGMs, including representation, inference and learning principles, and reviews real-world applications for each type of model. These applications are drawn from a broad range of disciplines, highlighting the many uses of Bayesian classifiers, hidden Markov models, Bayesian networks, dynamic and temporal Bayesian networks, Markov random fields, influence diagrams, and Markov decision processes.

Topics and features: presents a unified framework encompassing all of the main classes of PGMs; explores the fundamental aspects of representation, inference and learning for each technique; describes the practical application of the different techniques; examines the latest developments in the field, covering multidimensional Bayesian classifiers, relational graphical models and causal models; provides exercises, suggestions for further reading, and ideas for research or programming projects at the end of each chapter; suggests possible course outlines for instructors in the preface.

This classroom-tested work is suitable as a textbook for an advanced undergraduate or a graduate course in probabilistic graphical models for students of computer science, engineering, and physics. Professionals wishing to apply probabilistic graphical models in their own field, or interested in the basis of these techniques, will also find the book to be an invaluable reference.

Автор: Whittaker, Joe
Название: Graphical models in applied multivariate statistics
ISBN: 0470743662 ISBN-13(EAN): 9780470743669
Издательство: Wiley
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Цена: 70700.00 T
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Описание: - It reveals the interrelationships between multiple variables and features of the underlying conditional independence. - It covers conditional independence, several types of independence graphs, Gaussian models, issues in model selection, regression and decomposition. - Many numerical examples and exercises with solutions are included.

Автор: Zucchini
Название: Hidden Markov Models for Time Series
ISBN: 1482253836 ISBN-13(EAN): 9781482253832
Издательство: Taylor&Francis
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Цена: 93910.00 T
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Описание: Hidden Markov Models (HMMs) remains a vibrant area of research in statistics, with many new applications appearing since publication of the first edition.

Автор: Sucar Luis Enrique
Название: Probabilistic Graphical Models: Principles and Applications
ISBN: 3030619451 ISBN-13(EAN): 9783030619459
Издательство: Springer
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Цена: 46570.00 T
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Описание:

Part I: Fundamentals

Introduction

Probability Theory

Graph Theory

Part II: Probabilistic Models

Bayesian Classifiers

Hidden Markov Models

Markov Random Fields

Bayesian Networks: Representation and Inference

Bayesian Networks: Learning

Dynamic and Temporal Bayesian Networks

Part III: Decision Models

Decision Graphs

Markov Decision Processes

Partially Observable Markov Decision Processes

Part IV: Relational, Causal and Deep Models

Relational Probabilistic Graphical Models

Graphical Causal Models

Causal Discovery

Deep Learning and Graphical Models

A: A Python Library for Inference and Learning

Glossary

Index

Автор: Maathuis, Marloes
Название: Handbook of Graphical Models
ISBN: 0367732602 ISBN-13(EAN): 9780367732608
Издательство: Taylor&Francis
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Цена: 63280.00 T
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Автор: Wills Graham
Название: Visualizing Time: Designing Graphical Representations for Statistical Data
ISBN: 1493939246 ISBN-13(EAN): 9781493939244
Издательство: Springer
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Цена: 46570.00 T
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Описание: He does not simply give rules and advice, but bases these on general principles and provide a clear path between them This book is concerned with the graphical representation of time data and is written to cover a range of different users.

Автор: Harvey, A.c.
Название: Forecasting, structural time series models, and the kalman filter
ISBN: 0521321964 ISBN-13(EAN): 9780521321969
Издательство: Cambridge Academ
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Цена: 142560.00 T
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Описание: This book is concerned with modelling economic and social time series and with addressing the special problems which the treatment of such series pose. It is unique in its use of Kalman filtering with econometric and time series modelling.

Автор: Meleard Sylvie
Название: Stochastic Models for Structured Populations
ISBN: 3319217100 ISBN-13(EAN): 9783319217109
Издательство: Springer
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Цена: 37260.00 T
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Описание: Stochastic Models for Structured Populations

Автор: Christophe Chorro; Dominique Gu?gan; Florian Ielpo
Название: A Time Series Approach to Option Pricing
ISBN: 3662450364 ISBN-13(EAN): 9783662450369
Издательство: Springer
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Цена: 93160.00 T
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Описание: The Black Scholes framework is introduced and by underlining its shortcomings, an alternative approach is presented that has emerged over the past ten years of academic research, an approach that is much more grounded on a realistic statistical analysis of data rather than on ad hoc tractable continuous time option pricing models.