The Poisson Dirichlet Distribution And Related Topics

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The Poisson Dirichlet Distribution And Related Topics
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Author : Shui Feng
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-05-27
The Poisson Dirichlet Distribution And Related Topics written by Shui Feng and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-27 with Mathematics categories.
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.
Partitions Hypergeometric Systems And Dirichlet Processes In Statistics
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Author : Shuhei Mano
language : en
Publisher: Springer
Release Date : 2018-07-12
Partitions Hypergeometric Systems And Dirichlet Processes In Statistics written by Shuhei Mano and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-12 with Mathematics categories.
This book focuses on statistical inferences related to various combinatorial stochastic processes. Specifically, it discusses the intersection of three subjects that are generally studied independently of each other: partitions, hypergeometric systems, and Dirichlet processes. The Gibbs partition is a family of measures on integer partition, and several prior processes, such as the Dirichlet process, naturally appear in connection with infinite exchangeable Gibbs partitions. Examples include the distribution on a contingency table with fixed marginal sums and the conditional distribution of Gibbs partition given the length. The A-hypergeometric distribution is a class of discrete exponential families and appears as the conditional distribution of a multinomial sample from log-affine models. The normalizing constant is the A-hypergeometric polynomial, which is a solution of a system of linear differential equations of multiple variables determined by a matrix A, called A-hypergeometric system. The book presents inference methods based on the algebraic nature of the A-hypergeometric system, and introduces the holonomic gradient methods, which numerically solve holonomic systems without combinatorial enumeration, to compute the normalizing constant. Furher, it discusses Markov chain Monte Carlo and direct samplers from A-hypergeometric distribution, as well as the maximum likelihood estimation of the A-hypergeometric distribution of two-row matrix using properties of polytopes and information geometry. The topics discussed are simple problems, but the interdisciplinary approach of this book appeals to a wide audience with an interest in statistical inference on combinatorial stochastic processes, including statisticians who are developing statistical theories and methodologies, mathematicians wanting to discover applications of their theoretical results, and researchers working in various fields of data sciences.
Pioneering Works On Distribution Theory
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Author : Nobuaki Hoshino
language : en
Publisher: Springer Nature
Release Date : 2021-01-04
Pioneering Works On Distribution Theory written by Nobuaki Hoshino and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-04 with Mathematics categories.
This book highlights the forefront of research on statistical distribution theory, with a focus on unconventional random quantities, and on phenomena such as random partitioning. The respective papers reflect the continuing appeal of distribution theory and the lively interest in this classic field, which owes much of its expansion since the 1960s to Professor Masaaki Sibuya, to whom this book is dedicated. The topics addressed include a test procedure for discriminating the (multivariate) Ewens distribution from the Pitman Sampling Formula, approximation to the length of the Ewens distribution by discrete distributions and the normal distribution, and the distribution of the number of levels in [s]-specified random permutations. Also included are distributions associated with orthogonal polynomials with a symmetric matrix argument and the characterization of the Jeffreys prior.
New Trends In Stochastic Analysis And Related Topics
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Author : Huaizhong Zhao
language : en
Publisher: World Scientific
Release Date : 2012
New Trends In Stochastic Analysis And Related Topics written by Huaizhong Zhao and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Mathematics categories.
The volume is dedicated to Professor David Elworthy to celebrate his fundamental contribution and exceptional influence on stochastic analysis and related fields. Stochastic analysis has been profoundly developed as a vital fundamental research area in mathematics in recent decades. It has been discovered to have intrinsic connections with many other areas of mathematics such as partial differential equations, functional analysis, topology, differential geometry, dynamical systems, etc. Mathematicians developed many mathematical tools in stochastic analysis to understand and model random phenomena in physics, biology, finance, fluid, environment science, etc. This volume contains 12 comprehensive review/new articles written by world leading researchers (by invitation) and their collaborators. It covers stochastic analysis on manifolds, rough paths, Dirichlet forms, stochastic partial differential equations, stochastic dynamical systems, infinite dimensional analysis, stochastic flows, quantum stochastic analysis and stochastic Hamilton Jacobi theory. Articles contain cutting edge research methodology, results and ideas in relevant fields. They are of interest to research mathematicians and postgraduate students in stochastic analysis, probability, partial differential equations, dynamical systems, mathematical physics, as well as to physicists, financial mathematicians, engineers, etc.
Nonparametric Statistical Methods And Related Topics
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Author : Francisco J. Samaniego
language : en
Publisher: World Scientific
Release Date : 2011
Nonparametric Statistical Methods And Related Topics written by Francisco J. Samaniego and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Mathematics categories.
Review papers. 1. On the scholarly work of P.K. Bhattacharya / P. Hall and F.J. Samaniego. 2. The propensity score and its role in causal inference / C. Drake and T. Loux. 3. Recent tests for symmetry with multivariate and structured data: a review / S.G. Meintanis and J. Ngatchou-Wandji -- Papers on general nonparametric inference. 4. On robust versions of classical tests with dependent data / J. Jiang. 5. Density estimation by sampling from stationary continuous time parameter associated processes / G.G. Roussas and D. Bhattacharya. 6. A Short proof of the Feigin-Tweedie theorem on the existence of the mean functional of a Dirichlet process / J. Sethuraman. 7. Max-min Bernstein polynomial estimation of a discontinuity in distribution / K.-S. Song. 8. U-statistics based on higher-order spacings / D.D. Tung and S.R. Jammalamadaka. 9. Nonparametric models for non-Gaussian longitudinal data / N. Zhang, H.-G. Muller and J.-L. Wang -- Papers on aspects of linear or generalized linear models. 10. Better residuals / R. Beran. 11. The use of Peters-Belson regression in legal cases / E. Bura, J.L. Gastwirth and H. Hikawa. 12. On a hybrid approach to parametric and nonparametric regression / P. Burman and P. Chaudhuri. 13. Nonparametric regression models with integrated covariates / Z. Cai. 14. A dynamic test for misspecification of a linear model / M.P. McAssey and F. Hsieh. 15. The principal component decomposition of the basic martingale / W. Stute -- Papers on time series analysis. 16. Fast scatterplot smoothing using blockwise least squares fitting / A. Aue and T.C.M. Lee. 17. Some recent advances in semiparametric estimation of the GARCH model / J. Di and A. Gangopadhyay. 18. Extreme dependence in multivariate time series: a review / R. Sen and Z. Tan. 19. Dynamic mixed models for irregularly observed water quality data / R.H. Shumway -- Papers on asymptotic theory. 20. Asymptotic behavior of the kernel density estimators for nonstationary dependent random variables with binned data / J.-F. Lenain, M. Harel and M.L. Puri. 21. Convergence rates of an improved isotonic regression estimator / H. Mukerjee. 22. Asymptotic distribution of the smallest eigenvalue of Wishart(N, n) When N, n ' [symbol] such that N/n --> 0 / D. Paul
Fundamentals Of Nonparametric Bayesian Inference
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Author : Subhashis Ghosal
language : en
Publisher: Cambridge University Press
Release Date : 2017-06-26
Fundamentals Of Nonparametric Bayesian Inference written by Subhashis Ghosal and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-26 with Business & Economics categories.
Bayesian nonparametrics comes of age with this landmark text synthesizing theory, methodology and computation.
Probabilistic Foundations Of Statistical Network Analysis
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Author : Harry Crane
language : en
Publisher: CRC Press
Release Date : 2018-04-17
Probabilistic Foundations Of Statistical Network Analysis written by Harry Crane and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-17 with Business & Economics categories.
Probabilistic Foundations of Statistical Network Analysis presents a fresh and insightful perspective on the fundamental tenets and major challenges of modern network analysis. Its lucid exposition provides necessary background for understanding the essential ideas behind exchangeable and dynamic network models, network sampling, and network statistics such as sparsity and power law, all of which play a central role in contemporary data science and machine learning applications. The book rewards readers with a clear and intuitive understanding of the subtle interplay between basic principles of statistical inference, empirical properties of network data, and technical concepts from probability theory. Its mathematically rigorous, yet non-technical, exposition makes the book accessible to professional data scientists, statisticians, and computer scientists as well as practitioners and researchers in substantive fields. Newcomers and non-quantitative researchers will find its conceptual approach invaluable for developing intuition about technical ideas from statistics and probability, while experts and graduate students will find the book a handy reference for a wide range of new topics, including edge exchangeability, relative exchangeability, graphon and graphex models, and graph-valued Levy process and rewiring models for dynamic networks. The author’s incisive commentary supplements these core concepts, challenging the reader to push beyond the current limitations of this emerging discipline. With an approachable exposition and more than 50 open research problems and exercises with solutions, this book is ideal for advanced undergraduate and graduate students interested in modern network analysis, data science, machine learning, and statistics. Harry Crane is Associate Professor and Co-Director of the Graduate Program in Statistics and Biostatistics and an Associate Member of the Graduate Faculty in Philosophy at Rutgers University. Professor Crane’s research interests cover a range of mathematical and applied topics in network science, probability theory, statistical inference, and mathematical logic. In addition to his technical work on edge and relational exchangeability, relative exchangeability, and graph-valued Markov processes, Prof. Crane’s methods have been applied to domain-specific cybersecurity and counterterrorism problems at the Foreign Policy Research Institute and RAND’s Project AIR FORCE.
Probability And Mathematical Genetics
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Author : N. H. Bingham
language : en
Publisher: Cambridge University Press
Release Date : 2010-07-15
Probability And Mathematical Genetics written by N. H. Bingham and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-15 with Mathematics categories.
No leading university department of mathematics or statistics, or library, can afford to be without this unique text. Leading authorities give a unique insight into a wide range of currently topical problems, from the mathematics of road networks to the genomics of cancer.
Stochastic Differential Equations In Infinite Dimensions
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Author : Leszek Gawarecki
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-11-29
Stochastic Differential Equations In Infinite Dimensions written by Leszek Gawarecki and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-29 with Mathematics categories.
The systematic study of existence, uniqueness, and properties of solutions to stochastic differential equations in infinite dimensions arising from practical problems characterizes this volume that is intended for graduate students and for pure and applied mathematicians, physicists, engineers, professionals working with mathematical models of finance. Major methods include compactness, coercivity, monotonicity, in a variety of set-ups. The authors emphasize the fundamental work of Gikhman and Skorokhod on the existence and uniqueness of solutions to stochastic differential equations and present its extension to infinite dimension. They also generalize the work of Khasminskii on stability and stationary distributions of solutions. New results, applications, and examples of stochastic partial differential equations are included. This clear and detailed presentation gives the basics of the infinite dimensional version of the classic books of Gikhman and Skorokhod and of Khasminskii in one concise volume that covers the main topics in infinite dimensional stochastic PDE’s. By appropriate selection of material, the volume can be adapted for a 1- or 2-semester course, and can prepare the reader for research in this rapidly expanding area.
Measure Valued Branching Markov Processes
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Author : Zenghu Li
language : en
Publisher: Springer Nature
Release Date : 2023-03-13
Measure Valued Branching Markov Processes written by Zenghu Li and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-13 with Mathematics categories.
This book provides a compact introduction to the theory of measure-valued branching processes, immigration processes and Ornstein–Uhlenbeck type processes. Measure-valued branching processes arise as high density limits of branching particle systems. The first part of the book gives an analytic construction of a special class of such processes, the Dawson–Watanabe superprocesses, which includes the finite-dimensional continuous-state branching process as an example. Under natural assumptions, it is shown that the superprocesses have Borel right realizations. Transformations are then used to derive the existence and regularity of several different forms of the superprocesses. This technique simplifies the constructions and gives useful new perspectives. Martingale problems of superprocesses are discussed under Feller type assumptions. The second part investigates immigration structures associated with the measure-valued branching processes. The structures are formulated by skew convolution semigroups, which are characterized in terms of infinitely divisible probability entrance laws. A theory of stochastic equations for one-dimensional continuous-state branching processes with or without immigration is developed, which plays a key role in the construction of measure flows of those processes. The third part of the book studies a class of Ornstein-Uhlenbeck type processes in Hilbert spaces defined by generalized Mehler semigroups, which arise naturally in fluctuation limit theorems of the immigration superprocesses. This volume is aimed at researchers in measure-valued processes, branching processes, stochastic analysis, biological and genetic models, and graduate students in probability theory and stochastic processes.