Stochastic Modelling Of Social Processes
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| Author | : Andreas Diekmann |
| Publisher | : Academic Press |
| Total Pages | : 352 |
| Release | : 2014-05-10 |
| Genre | : Mathematics |
| ISBN | : 1483266567 |
Stochastic Modelling of Social Processes provides information pertinent to the development in the field of stochastic modeling and its applications in the social sciences. This book demonstrates that stochastic models can fulfill the goals of explanation and prediction. Organized into nine chapters, this book begins with an overview of stochastic models that fulfill normative, predictive, and structural–analytic roles with the aid of the theory of probability. This text then examines the study of labor market structures using analysis of job and career mobility, which is one of the approaches taken by sociologists in research on the labor market. Other chapters consider the characteristic trends and patterns from data on divorces. This book discusses as well the two approaches of stochastic modeling of social processes, namely competing risk models and semi-Markov processes. The final chapter deals with the practical application of regression models of survival data. This book is a valuable resource for social scientists and statisticians.
| Author | : David J. Bartholomew |
| Publisher | : Chichester ; New York : Wiley |
| Total Pages | : 392 |
| Release | : 1982 |
| Genre | : Mathematics |
| ISBN | : |
| Author | : Oliver Ibe |
| Publisher | : Newnes |
| Total Pages | : 515 |
| Release | : 2013-05-22 |
| Genre | : Mathematics |
| ISBN | : 0124078397 |
Markov processes are processes that have limited memory. In particular, their dependence on the past is only through the previous state. They are used to model the behavior of many systems including communications systems, transportation networks, image segmentation and analysis, biological systems and DNA sequence analysis, random atomic motion and diffusion in physics, social mobility, population studies, epidemiology, animal and insect migration, queueing systems, resource management, dams, financial engineering, actuarial science, and decision systems. Covering a wide range of areas of application of Markov processes, this second edition is revised to highlight the most important aspects as well as the most recent trends and applications of Markov processes. The author spent over 16 years in the industry before returning to academia, and he has applied many of the principles covered in this book in multiple research projects. Therefore, this is an applications-oriented book that also includes enough theory to provide a solid ground in the subject for the reader. - Presents both the theory and applications of the different aspects of Markov processes - Includes numerous solved examples as well as detailed diagrams that make it easier to understand the principle being presented - Discusses different applications of hidden Markov models, such as DNA sequence analysis and speech analysis.
| Author | : Howard M. Taylor |
| Publisher | : Academic Press |
| Total Pages | : 410 |
| Release | : 2014-05-10 |
| Genre | : Mathematics |
| ISBN | : 1483269272 |
An Introduction to Stochastic Modeling provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich diversity of applications of stochastic processes in the sciences. Organized into nine chapters, this book begins with an overview of diverse types of stochastic models, which predicts a set of possible outcomes weighed by their likelihoods or probabilities. This text then provides exercises in the applications of simple stochastic analysis to appropriate problems. Other chapters consider the study of general functions of independent, identically distributed, nonnegative random variables representing the successive intervals between renewals. This book discusses as well the numerous examples of Markov branching processes that arise naturally in various scientific disciplines. The final chapter deals with queueing models, which aid the design process by predicting system performance. This book is a valuable resource for students of engineering and management science. Engineers will also find this book useful.
| Author | : Nicolas Lanchier |
| Publisher | : Springer |
| Total Pages | : 305 |
| Release | : 2017-01-27 |
| Genre | : Mathematics |
| ISBN | : 3319500384 |
Three coherent parts form the material covered in this text, portions of which have not been widely covered in traditional textbooks. In this coverage the reader is quickly introduced to several different topics enriched with 175 exercises which focus on real-world problems. Exercises range from the classics of probability theory to more exotic research-oriented problems based on numerical simulations. Intended for graduate students in mathematics and applied sciences, the text provides the tools and training needed to write and use programs for research purposes. The first part of the text begins with a brief review of measure theory and revisits the main concepts of probability theory, from random variables to the standard limit theorems. The second part covers traditional material on stochastic processes, including martingales, discrete-time Markov chains, Poisson processes, and continuous-time Markov chains. The theory developed is illustrated by a variety of examples surrounding applications such as the gambler’s ruin chain, branching processes, symmetric random walks, and queueing systems. The third, more research-oriented part of the text, discusses special stochastic processes of interest in physics, biology, and sociology. Additional emphasis is placed on minimal models that have been used historically to develop new mathematical techniques in the field of stochastic processes: the logistic growth process, the Wright –Fisher model, Kingman’s coalescent, percolation models, the contact process, and the voter model. Further treatment of the material explains how these special processes are connected to each other from a modeling perspective as well as their simulation capabilities in C and MatlabTM.
| Author | : Dirk Helbing |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 351 |
| Release | : 2010-11-15 |
| Genre | : Mathematics |
| ISBN | : 3642115462 |
When I wrote the book Quantitative Sociodynamics, it was an early attempt to make methods from statistical physics and complex systems theory fruitful for the modeling and understanding of social phenomena. Unfortunately, the ?rst edition appeared at a quite prohibitive price. This was one reason to make these chapters available again by a new edition. The other reason is that, in the meantime, many of the methods discussed in this book are more and more used in a variety of different ?elds. Among the ideas worked out in this book are: 1 • a statistical theory of binary social interactions, • a mathematical formulation of social ?eld theory, which is the basis of social 2 force models, • a microscopic foundation of evolutionary game theory, based on what is known today as ‘proportional imitation rule’, a stochastic treatment of interactions in evolutionary game theory, and a model for the self-organization of behavioral 3 conventions in a coordination game. It, therefore, appeared reasonable to make this book available again, but at a more affordable price. To keep its original character, the translation of this book, which 1 D. Helbing, Interrelations between stochastic equations for systems with pair interactions. Ph- icaA 181, 29–52 (1992); D. Helbing, Boltzmann-like and Boltzmann-Fokker-Planck equations as a foundation of behavioral models. PhysicaA 196, 546–573 (1993). 2 D. Helbing, Boltzmann-like and Boltzmann-Fokker-Planck equations as a foundation of beh- ioral models. PhysicaA 196, 546–573 (1993); D.
| Author | : Uday B. Desai |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 310 |
| Release | : 1986-10-31 |
| Genre | : Science |
| ISBN | : 9780898381771 |
The subject of modelling and application of stochastic processes is too vast to be exhausted in a single volume. In this book, attention is focused on a small subset of this vast subject. The primary emphasis is on realization and approximation of stochastic systems. Recently there has been considerable interest in the stochastic realization problem, and hence, an attempt has been made here to collect in one place some of the more recent approaches and algorithms for solving the stochastic realiza tion problem. Various different approaches for realizing linear minimum-phase systems, linear nonminimum-phase systems, and bilinear systems are presented. These approaches range from time-domain methods to spectral-domain methods. An overview of the chapter contents briefly describes these approaches. Also, in most of these chapters special attention is given to the problem of developing numerically ef ficient algorithms for obtaining reduced-order (approximate) stochastic realizations. On the application side, chapters on use of Markov random fields for modelling and analyzing image signals, use of complementary models for the smoothing problem with missing data, and nonlinear estimation are included. Chapter 1 by Klein and Dickinson develops the nested orthogonal state space realization for ARMA processes. As suggested by the name, nested orthogonal realizations possess two key properties; (i) the state variables are orthogonal, and (ii) the system matrices for the (n + l)st order realization contain as their "upper" n-th order blocks the system matrices from the n-th order realization (nesting property).
| Author | : Nancy Brandon Tuma |
| Publisher | : Elsevier |
| Total Pages | : 602 |
| Release | : 1984-08-28 |
| Genre | : Technology & Engineering |
| ISBN | : 0323156908 |
Social Dynamics: Models and Methods focuses on sociological methodology and on the practice of sociological research. This book is organized into three parts encompassing 16 chapters that deal with the basic principles of social dynamics. The first part of this book considers the development of models and methods for causal analysis of the actual time paths of change in attributes of individual and social systems. This part also discusses the applications in which the use of dynamic models and methods seems to have enhanced the capacity to formulate and test sociological arguments. These models and methods are useful for answering questions about the detailed structure of social change processes. The second part explores the formulation of the continuous-time models of change in both quantitative and qualitative outcomes and the development of suitable methods for estimating these models from the kinds of data commonly available to sociologists. The third part describes a stochastic framework for analyzing both qualitative and quantitative outcome of social changes. This part also discusses the sociologists' perspective on the empirical study of social change processes. This text will be of great value to sociologists and sociological researchers.
| Author | : Hossein Bonakdari |
| Publisher | : Elsevier |
| Total Pages | : 372 |
| Release | : 2022-04-13 |
| Genre | : Science |
| ISBN | : 0323972756 |
Stochastic Modeling: A Thorough Guide to Evaluate, Pre-Process, Model and Compare Time Series with MATLAB Software allows for new avenues in time series analysis and predictive modeling which summarize more than ten years of experience in the application of stochastic models in environmental problems. The book introduces a variety of different topics in time series in the modeling and prediction of complex environmental systems. Most importantly, all codes are user-friendly and readers will be able to use them for their cases. Users who may not be familiar with MATLAB software can also refer to the appendix. This book also guides the reader step-by-step to learn developed codes for time series modeling, provides required toolboxes, explains concepts, and applies different tools for different types of environmental time series problems. - Provides video tutorials on the use of codes - Includes a companion site with 3,000 lines of programming, 70 principal codes and 100 pseudo codes - Highlights multiple methods to Illustrate each problem
| Author | : Shunji Osaki |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 338 |
| Release | : 2012-11-02 |
| Genre | : Mathematics |
| ISBN | : 3540248080 |
Our daily lives can be maintained by the high-technology systems. Computer systems are typical examples of such systems. We can enjoy our modern lives by using many computer systems. Much more importantly, we have to maintain such systems without failure, but cannot predict when such systems will fail and how to fix such systems without delay. A stochastic process is a set of outcomes of a random experiment indexed by time, and is one of the key tools needed to analyze the future behavior quantitatively. Reliability and maintainability technologies are of great interest and importance to the maintenance of such systems. Many mathematical models have been and will be proposed to describe reliability and maintainability systems by using the stochastic processes. The theme of this book is "Stochastic Models in Reliability and Main tainability. " This book consists of 12 chapters on the theme above from the different viewpoints of stochastic modeling. Chapter 1 is devoted to "Renewal Processes," under which classical renewal theory is surveyed and computa tional methods are described. Chapter 2 discusses "Stochastic Orders," and in it some definitions and concepts on stochastic orders are described and ag ing properties can be characterized by stochastic orders. Chapter 3 is devoted to "Classical Maintenance Models," under which the so-called age, block and other replacement models are surveyed. Chapter 4 discusses "Modeling Plant Maintenance," describing how maintenance practice can be carried out for plant maintenance.
