Random Growth Models

Random Growth Models

Author: Michael Damron

Publisher: American Mathematical Soc.

Published: 2018-09-27

Total Pages: 274

ISBN-13: 1470435535

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The study of random growth models began in probability theory about 50 years ago, and today this area occupies a central place in the subject. The considerable challenges posed by these models have spurred the development of innovative probability theory and opened up connections with several other parts of mathematics, such as partial differential equations, integrable systems, and combinatorics. These models also have applications to fields such as computer science, biology, and physics. This volume is based on lectures delivered at the 2017 AMS Short Course “Random Growth Models”, held January 2–3, 2017 in Atlanta, GA. The articles in this book give an introduction to the most-studied models; namely, first- and last-passage percolation, the Eden model of cell growth, and particle systems, focusing on the main research questions and leading up to the celebrated Kardar-Parisi-Zhang equation. Topics covered include asymptotic properties of infection times, limiting shape results, fluctuation bounds, and geometrical properties of geodesics, which are optimal paths for growth.


Random Growth Models

Random Growth Models

Author: Michael Damron

Publisher:

Published: 2018

Total Pages: 274

ISBN-13: 9781470449070

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The study of random growth models began in probability theory about 50 years ago, and today this area occupies a central place in the subject. The considerable challenges posed by these models have spurred the development of innovative probability theory and opened up connections with several other parts of mathematics, such as partial differential equations, integrable systems, and combinatorics. These models also have applications to fields such as computer science, biology, and physics. This volume is based on lectures delivered at the 2017 AMS Short Course ""Random Growth Models"", held Ja.


Growth Modeling

Growth Modeling

Author: Kevin J. Grimm

Publisher: Guilford Publications

Published: 2016-10-17

Total Pages: 558

ISBN-13: 1462526063

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Growth models are among the core methods for analyzing how and when people change. Discussing both structural equation and multilevel modeling approaches, this book leads readers step by step through applying each model to longitudinal data to answer particular research questions. It demonstrates cutting-edge ways to describe linear and nonlinear change patterns, examine within-person and between-person differences in change, study change in latent variables, identify leading and lagging indicators of change, evaluate co-occurring patterns of change across multiple variables, and more. User-friendly features include real data examples, code (for Mplus or NLMIXED in SAS, and OpenMx or nlme in R), discussion of the output, and interpretation of each model's results. User-Friendly Features *Real, worked-through longitudinal data examples serving as illustrations in each chapter. *Script boxes that provide code for fitting the models to example data and facilitate application to the reader's own data. *"Important Considerations" sections offering caveats, warnings, and recommendations for the use of specific models. *Companion website supplying datasets and syntax for the book's examples, along with additional code in SAS/R for linear mixed-effects modeling.


Random Matrices, Random Processes and Integrable Systems

Random Matrices, Random Processes and Integrable Systems

Author: John Harnad

Publisher: Springer Science & Business Media

Published: 2011-05-06

Total Pages: 536

ISBN-13: 1441995145

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This book explores the remarkable connections between two domains that, a priori, seem unrelated: Random matrices (together with associated random processes) and integrable systems. The relations between random matrix models and the theory of classical integrable systems have long been studied. These appear mainly in the deformation theory, when parameters characterizing the measures or the domain of localization of the eigenvalues are varied. The resulting differential equations determining the partition function and correlation functions are, remarkably, of the same type as certain equations appearing in the theory of integrable systems. They may be analyzed effectively through methods based upon the Riemann-Hilbert problem of analytic function theory and by related approaches to the study of nonlinear asymptotics in the large N limit. Associated with studies of matrix models are certain stochastic processes, the "Dyson processes", and their continuum diffusion limits, which govern the spectrum in random matrix ensembles, and may also be studied by related methods. Random Matrices, Random Processes and Integrable Systems provides an in-depth examination of random matrices with applications over a vast variety of domains, including multivariate statistics, random growth models, and many others. Leaders in the field apply the theory of integrable systems to the solution of fundamental problems in random systems and processes using an interdisciplinary approach that sheds new light on a dynamic topic of current research.


The Random-Cluster Model

The Random-Cluster Model

Author: Geoffrey R. Grimmett

Publisher: Springer Science & Business Media

Published: 2006-12-13

Total Pages: 392

ISBN-13: 3540328912

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The random-cluster model has emerged as a key tool in the mathematical study of ferromagnetism. It may be viewed as an extension of percolation to include Ising and Potts models, and its analysis is a mix of arguments from probability and geometry. The Random-Cluster Model contains accounts of the subcritical and supercritical phases, together with clear statements of important open problems. The book includes treatment of the first-order (discontinuous) phase transition.


The Oxford Handbook of Random Matrix Theory

The Oxford Handbook of Random Matrix Theory

Author: Gernot Akemann

Publisher: Oxford Handbooks

Published: 2015-08-09

Total Pages: 0

ISBN-13: 9780198744191

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With a foreword by Freeman Dyson, the handbook brings together leading mathematicians and physicists to offer a comprehensive overview of random matrix theory, including a guide to new developments and the diverse range of applications of this approach.In part one, all modern and classical techniques of solving random matrix models are explored, including orthogonal polynomials, exact replicas or supersymmetry.


Advances in Growth Curve Models

Advances in Growth Curve Models

Author: Ratan Dasgupta

Publisher: Springer Science & Business Media

Published: 2013-07-23

Total Pages: 278

ISBN-13: 1461468620

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Advances in Growth Curve Models: Topics from the Indian Statistical Institute is developed from the Indian Statistical Institute's A National Conference on Growth Curve Models. This conference took place between March 28-30, 2012 in Giridih, Jharkhand, India. Jharkhand is a tribal area. Advances in Growth Curve Models: Topics from the Indian Statistical Institute shares the work of researchers in growth models used in multiple fields. A growth curve is an empirical model of the evolution of a quantity over time. Case studies and theoretical findings, important applications in everything from health care to population projection, form the basis of this volume. Growth curves in longitudinal studies are widely used in many disciplines including: Biology, Population studies, Economics, Biological Sciences, SQC, Sociology, Nano-biotechnology, and Fluid mechanics. Some included reports are research topics that have just been developed, whereas others present advances in existing literature. Both included tools and techniques will assist students and researchers in their future work. Also included is a discussion of future applications of growth curve models.