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Introduction to Graphical Modelling

2012-12-06 Mathematics
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Release : 2012-12-06
Genre : Mathematics
Kind : eBook
Book Rating : 933/5 ( reviews)

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Book Synopsis Introduction to Graphical Modelling by : David Edwards

Download or read book Introduction to Graphical Modelling written by David Edwards. This book was released on 2012-12-06. Available in PDF, EPUB and Kindle. Book excerpt: A useful introduction to this topic for both students and researchers, with an emphasis on applications and practicalities rather than on a formal development. It is based on the popular software package for graphical modelling, MIM, freely available for downloading from the Internet. Following a description of some of the basic ideas of graphical modelling, subsequent chapters describe particular families of models, including log-linear models, Gaussian models, and models for mixed discrete and continuous variables. Further chapters cover hypothesis testing and model selection. Chapters 7 and 8 are new to this second edition and describe the use of directed, chain, and other graphs, complete with a summary of recent work on causal inference.

Linear and Graphical Models

1995-05-19 Mathematics
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Release : 1995-05-19
Genre : Mathematics
Kind : eBook
Book Rating : 217/5 ( reviews)

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Book Synopsis Linear and Graphical Models by : Heidi H. Andersen

Download or read book Linear and Graphical Models written by Heidi H. Andersen. This book was released on 1995-05-19. Available in PDF, EPUB and Kindle. Book excerpt: In the last decade, graphical models have become increasingly popular as a statistical tool. This book is the first which 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 parameter estimation and hypothesis testing for these models. After introducing undirected graphs, they then develop the theory of complex normal graphical models including the maximum likelihood estimation of the concentration matrix and hypothesis testing of conditional independence.

Linear and Graphical Models

2012-12-06 Mathematics
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Release : 2012-12-06
Genre : Mathematics
Kind : eBook
Book Rating : 401/5 ( reviews)

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Book Synopsis Linear and Graphical Models by : Heidi H. Andersen

Download or read book Linear and Graphical Models written by Heidi H. Andersen. This book was released on 2012-12-06. Available in PDF, EPUB and Kindle. Book excerpt: In the last decade, graphical models have become increasingly popular as a statistical tool. This book is the first which 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 parameter estimation and hypothesis testing for these models. After introducing undirected graphs, they then develop the theory of complex normal graphical models including the maximum likelihood estimation of the concentration matrix and hypothesis testing of conditional independence.

Handbook of Graphical Models

2018-11-12 Mathematics
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Release : 2018-11-12
Genre : Mathematics
Kind : eBook
Book Rating : 235/5 ( reviews)

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Book Synopsis Handbook of Graphical Models by : Marloes Maathuis

Download or read book Handbook of Graphical Models written by Marloes Maathuis. This book was released on 2018-11-12. Available in PDF, EPUB and Kindle. Book excerpt: A graphical model is a statistical model that is represented by a graph. The factorization properties underlying graphical models facilitate tractable computation with multivariate distributions, making the models a valuable tool with a plethora of applications. Furthermore, directed graphical models allow intuitive causal interpretations and have become a cornerstone for causal inference. While there exist a number of excellent books on graphical models, the field has grown so much that individual authors can hardly cover its entire scope. Moreover, the field is interdisciplinary by nature. Through chapters by leading researchers from different areas, this handbook provides a broad and accessible overview of the state of the art. Key features: * Contributions by leading researchers from a range of disciplines * Structured in five parts, covering foundations, computational aspects, statistical inference, causal inference, and applications * Balanced coverage of concepts, theory, methods, examples, and applications * Chapters can be read mostly independently, while cross-references highlight connections The handbook is targeted at a wide audience, including graduate students, applied researchers, and experts in graphical models.

Graphical Models

1996-05-02 Mathematics
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Release : 1996-05-02
Genre : Mathematics
Kind : eBook
Book Rating : 22X/5 ( reviews)

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Book Synopsis Graphical Models by : Steffen L. Lauritzen

Download or read book Graphical Models written by Steffen L. Lauritzen. This book was released on 1996-05-02. Available in PDF, EPUB and Kindle. Book excerpt: The idea of modelling systems using graph theory has its origin in several scientific areas: in statistical physics (the study of large particle systems), in genetics (studying inheritable properties of natural species), and in interactions in contingency tables. The use of graphical models in statistics has increased considerably over recent years and the theory has been greatly developed and extended. This book provides the first comprehensive and authoritative account of the theory of graphical models and is written by a leading expert in the field. It contains the fundamental graph theory required and a thorough study of Markov properties associated with various type of graphs. The statistical theory of log-linear and graphical models for contingency tables, covariance selection models, and graphical models with mixed discrete-continous variables in developed detail. Special topics, such as the application of graphical models to probabilistic expert systems, are described briefly, and appendices give details of the multivarate normal distribution and of the theory of regular exponential families. The author has recently been awarded the RSS Guy Medal in Silver 1996 for his innovative contributions to statistical theory and practice, and especially for his work on graphical models.

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