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Statistics Based On Dirichlet Processes And Related Topics
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Book Synopsis Statistics Based on Dirichlet Processes and Related Topics by : Hajime Yamato
Download or read book Statistics Based on Dirichlet Processes and Related Topics written by Hajime Yamato and published by Springer Nature. This book was released on 2020-07-17 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the properties associated with the Dirichlet process, describing its use a priori for nonparametric inference and the Bayes estimate to obtain limits for the estimable parameter. It presents the limits and the well-known U- and V-statistics as a convex combination of U-statistics, and by investigating this convex combination, it demonstrates these three statistics. Next, the book notes that the Dirichlet process gives the discrete distribution with probability one, even if the parameter of the process is continuous. Therefore, there are duplications among the sample from the distribution, which are discussed. Because sampling from the Dirichlet process is described sequentially, it can be described equivalently by the Chinese restaurant process. Using this process, the Donnelly–Tavaré–Griffiths formulas I and II are obtained, both of which give the Ewens’ sampling formula. The book then shows the convergence and approximation of the distribution for its number of distinct components. Lastly, it explains the interesting properties of the Griffiths–Engen–McCloskey distribution, which is related to the Dirichlet process and the Ewens’ sampling formula.
Book Synopsis Bayesian Nonparametrics by : J.K. Ghosh
Download or read book Bayesian Nonparametrics written by J.K. Ghosh and published by Springer Science & Business Media. This book was released on 2006-05-11 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first systematic treatment of Bayesian nonparametric methods and the theory behind them. It will also appeal to statisticians in general. The book is primarily aimed at graduate students and can be used as the text for a graduate course in Bayesian non-parametrics.
Book Synopsis The Poisson-Dirichlet Distribution and Related Topics by : Shui Feng
Download or read book The Poisson-Dirichlet Distribution and Related Topics written by Shui Feng and published by Springer. This book was released on 2012-09-05 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting a comprehensive study of the Poisson-Dirichlet distribution, this volume emphasizes recent progress in evolutionary dynamics and asymptotic behaviors. The self-contained text presents methods and techniques that appeal to researchers in a wide variety of subjects.
Book Synopsis Bayesian Nonparametrics by : Nils Lid Hjort
Download or read book Bayesian Nonparametrics written by Nils Lid Hjort and published by Cambridge University Press. This book was released on 2010-04-12 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian nonparametrics works - theoretically, computationally. The theory provides highly flexible models whose complexity grows appropriately with the amount of data. Computational issues, though challenging, are no longer intractable. All that is needed is an entry point: this intelligent book is the perfect guide to what can seem a forbidding landscape. Tutorial chapters by Ghosal, Lijoi and Prünster, Teh and Jordan, and Dunson advance from theory, to basic models and hierarchical modeling, to applications and implementation, particularly in computer science and biostatistics. These are complemented by companion chapters by the editors and Griffin and Quintana, providing additional models, examining computational issues, identifying future growth areas, and giving links to related topics. This coherent text gives ready access both to underlying principles and to state-of-the-art practice. Specific examples are drawn from information retrieval, NLP, machine vision, computational biology, biostatistics, and bioinformatics.
Book Synopsis Dirichlet and Related Distributions by : Kai Wang Ng
Download or read book Dirichlet and Related Distributions written by Kai Wang Ng and published by John Wiley & Sons. This book was released on 2011-05-03 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Dirichlet distribution appears in many areas of application, which include modelling of compositional data, Bayesian analysis, statistical genetics, and nonparametric inference. This book provides a comprehensive review of the Dirichlet distribution and two extended versions, the Grouped Dirichlet Distribution (GDD) and the Nested Dirichlet Distribution (NDD), arising from likelihood and Bayesian analysis of incomplete categorical data and survey data with non-response. The theoretical properties and applications are also reviewed in detail for other related distributions, such as the inverted Dirichlet distribution, Dirichlet-multinomial distribution, the truncated Dirichlet distribution, the generalized Dirichlet distribution, Hyper-Dirichlet distribution, scaled Dirichlet distribution, mixed Dirichlet distribution, Liouville distribution, and the generalized Liouville distribution. Key Features: Presents many of the results and applications that are scattered throughout the literature in one single volume. Looks at the most recent results such as survival function and characteristic function for the uniform distributions over the hyper-plane and simplex; distribution for linear function of Dirichlet components; estimation via the expectation-maximization gradient algorithm and application; etc. Likelihood and Bayesian analyses of incomplete categorical data by using GDD, NDD, and the generalized Dirichlet distribution are illustrated in detail through the EM algorithm and data augmentation structure. Presents a systematic exposition of the Dirichlet-multinomial distribution for multinomial data with extra variation which cannot be handled by the multinomial distribution. S-plus/R codes are featured along with practical examples illustrating the methods. Practitioners and researchers working in areas such as medical science, biological science and social science will benefit from this book.
Book Synopsis Practical Nonparametric and Semiparametric Bayesian Statistics by : Dipak D. Dey
Download or read book Practical Nonparametric and Semiparametric Bayesian Statistics written by Dipak D. Dey and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: A compilation of original articles by Bayesian experts, this volume presents perspectives on recent developments on nonparametric and semiparametric methods in Bayesian statistics. The articles discuss how to conceptualize and develop Bayesian models using rich classes of nonparametric and semiparametric methods, how to use modern computational tools to summarize inferences, and how to apply these methodologies through the analysis of case studies.
Book Synopsis Combinatorial Stochastic Processes by : Jim Pitman
Download or read book Combinatorial Stochastic Processes written by Jim Pitman and published by Springer Science & Business Media. This book was released on 2006-05-11 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this text is to bring graduate students specializing in probability theory to current research topics at the interface of combinatorics and stochastic processes. There is particular focus on the theory of random combinatorial structures such as partitions, permutations, trees, forests, and mappings, and connections between the asymptotic theory of enumeration of such structures and the theory of stochastic processes like Brownian motion and Poisson processes.
Book Synopsis Theory and Use of the EM Algorithm by : Maya R. Gupta
Download or read book Theory and Use of the EM Algorithm written by Maya R. Gupta and published by Now Publishers Inc. This book was released on 2011 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces the expectation-maximization (EM) algorithm and provides an intuitive and mathematically rigorous understanding of this method. Theory and Use of the EM Algorithm is designed to be useful to both the EM novice and the experienced EM user looking to better understand the method and its use.
Book Synopsis Fundamentals of Nonparametric Bayesian Inference by : Subhashis Ghosal
Download or read book Fundamentals of Nonparametric Bayesian Inference written by Subhashis Ghosal and published by Cambridge University Press. This book was released on 2017-06-26 with total page 671 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian nonparametrics comes of age with this landmark text synthesizing theory, methodology and computation.
Book Synopsis Applications of Topic Models by : Jordan Boyd-Graber
Download or read book Applications of Topic Models written by Jordan Boyd-Graber and published by Now Publishers. This book was released on 2017-07-13 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: Describes recent academic and industrial applications of topic models with the goal of launching a young researcher capable of building their own applications of topic models.
Download or read book Text Mining with R written by Julia Silge and published by "O'Reilly Media, Inc.". This book was released on 2017-06-12 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chapter 7. Case Study : Comparing Twitter Archives; Getting the Data and Distribution of Tweets; Word Frequencies; Comparing Word Usage; Changes in Word Use; Favorites and Retweets; Summary; Chapter 8. Case Study : Mining NASA Metadata; How Data Is Organized at NASA; Wrangling and Tidying the Data; Some Initial Simple Exploration; Word Co-ocurrences and Correlations; Networks of Description and Title Words; Networks of Keywords; Calculating tf-idf for the Description Fields; What Is tf-idf for the Description Field Words?; Connecting Description Fields to Keywords; Topic Modeling.
Book Synopsis Dirichlet Forms and Symmetric Markov Processes by : Masatoshi Fukushima
Download or read book Dirichlet Forms and Symmetric Markov Processes written by Masatoshi Fukushima and published by Walter de Gruyter. This book was released on 2011 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the publication of the first edition in 1994, this book has attracted constant interests from readers and is by now regarded as a standard reference for the theory of Dirichlet forms. For the present second edition, the authors not only revise
Book Synopsis Model-Based Clustering and Classification for Data Science by : Charles Bouveyron
Download or read book Model-Based Clustering and Classification for Data Science written by Charles Bouveyron and published by Cambridge University Press. This book was released on 2019-07-25 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cluster analysis finds groups in data automatically. Most methods have been heuristic and leave open such central questions as: how many clusters are there? Which method should I use? How should I handle outliers? Classification assigns new observations to groups given previously classified observations, and also has open questions about parameter tuning, robustness and uncertainty assessment. This book frames cluster analysis and classification in terms of statistical models, thus yielding principled estimation, testing and prediction methods, and sound answers to the central questions. It builds the basic ideas in an accessible but rigorous way, with extensive data examples and R code; describes modern approaches to high-dimensional data and networks; and explains such recent advances as Bayesian regularization, non-Gaussian model-based clustering, cluster merging, variable selection, semi-supervised and robust classification, clustering of functional data, text and images, and co-clustering. Written for advanced undergraduates in data science, as well as researchers and practitioners, it assumes basic knowledge of multivariate calculus, linear algebra, probability and statistics.
Book Synopsis Discovery Science by : Larisa Soldatova
Download or read book Discovery Science written by Larisa Soldatova and published by Springer. This book was released on 2018-10-22 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 21st International Conference on Discovery Science, DS 2018, held in Limassol, Cyprus, in October 2018, co-located with the International Symposium on Methodologies for Intelligent Systems, ISMIS 2018. The 30 full papers presented together with 5 abstracts of invited talks in this volume were carefully reviewed and selected from 71 submissions. The scope of the conference includes the development and analysis of methods for discovering scientific knowledge, coming from machine learning, data mining, intelligent data analysis, big data analysis as well as their application in various scientific domains. The papers are organized in the following topical sections: Classification; meta-learning; reinforcement learning; streams and time series; subgroup and subgraph discovery; text mining; and applications.
Book Synopsis Mining Text Data by : Charu C. Aggarwal
Download or read book Mining Text Data written by Charu C. Aggarwal and published by Springer Science & Business Media. This book was released on 2012-02-03 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique scenarios where text mining algorithms are learned. Mining Text Data introduces an important niche in the text analytics field, and is an edited volume contributed by leading international researchers and practitioners focused on social networks & data mining. This book contains a wide swath in topics across social networks & data mining. Each chapter contains a comprehensive survey including the key research content on the topic, and the future directions of research in the field. There is a special focus on Text Embedded with Heterogeneous and Multimedia Data which makes the mining process much more challenging. A number of methods have been designed such as transfer learning and cross-lingual mining for such cases. Mining Text Data simplifies the content, so that advanced-level students, practitioners and researchers in computer science can benefit from this book. Academic and corporate libraries, as well as ACM, IEEE, and Management Science focused on information security, electronic commerce, databases, data mining, machine learning, and statistics are the primary buyers for this reference book.
Book Synopsis Handbook of Mixed Membership Models and Their Applications by : Edoardo M. Airoldi
Download or read book Handbook of Mixed Membership Models and Their Applications written by Edoardo M. Airoldi and published by CRC Press. This book was released on 2014-11-06 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: Incorporating more than 20 years of the editors' and contributors' statistical work in mixed membership modeling, this handbook shows how to use these flexible modeling tools to uncover hidden patterns in modern high-dimensional multivariate data. It explores the use of the models in various application settings, including survey data, population genetics, text analysis, image processing and annotation, and molecular biology. Through examples using real data sets, readers will discover how to characterize complex multivariate data in a range of areas.
Book Synopsis Current Issues in Statistical Inference by : Dev Basu
Download or read book Current Issues in Statistical Inference written by Dev Basu and published by IMS. This book was released on 1992 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt:
