𝔖 Scriptorium
✦   LIBER   ✦

📁

Quasi-Stationary Distributions: Markov Chains, Diffusions and Dynamical Systems

✍ Scribed by Pierre Collet, Servet Martínez, Jaime San Martín (auth.)


Publisher
Springer-Verlag Berlin Heidelberg
Year
2013
Tongue
English
Leaves
287
Series
Probability and Its Applications
Edition
1
Category
Library

⬇  Acquire This Volume

No coin nor oath required. For personal study only.

✦ Synopsis


Main concepts of quasi-stationary distributions (QSDs) for killed processes are the focus of the present volume. For diffusions, the killing is at the boundary and for dynamical systems there is a trap. The authors present the QSDs as the ones that allow describing the long-term behavior conditioned to not being killed. Studies in this research area started with Kolmogorov and Yaglom and in the last few decades have received a great deal of attention. The authors provide the exponential distribution property of the killing time for QSDs, present the more general result on their existence and study the process of trajectories that survive forever. For birth-and-death chains and diffusions, the existence of a single or a continuum of QSDs is described. They study the convergence to the extremal QSD and give the classification of the survival process. In this monograph, the authors discuss Gibbs QSDs for symbolic systems and absolutely continuous QSDs for repellers.

The findings described are relevant to researchers in the fields of Markov chains, diffusions, potential theory, dynamical systems, and in areas where extinction is a central concept. The theory is illustrated with numerous examples. The volume uniquely presents the distribution behavior of individuals who survive in a decaying population for a very long time. It also provides the background for applications in mathematical ecology, statistical physics, computer sciences, and economics.

✦ Table of Contents


Front Matter....Pages I-XV
Introduction....Pages 1-15
Quasi-Stationary Distributions: General Results....Pages 17-29
Markov Chains on Finite Spaces....Pages 31-44
Markov Chains on Countable Spaces....Pages 45-68
Birth-and-Death Chains....Pages 69-111
Regular Diffusions on [0,∞)....Pages 113-195
Infinity as Entrance Boundary....Pages 197-226
Dynamical Systems....Pages 227-268
Back Matter....Pages 269-280

✦ Subjects


Probability Theory and Stochastic Processes; Dynamical Systems and Ergodic Theory; Genetics and Population Dynamics; Partial Differential Equations


📜 SIMILAR VOLUMES


Limit Theorems for Markov Chains and Sto
✍ Hubert Hennion, Loic Herve 📂 Library 📅 2001 🏛 Springer 🌐 English

This book shows how techniques from the perturbation theory of operators, applied to a quasi-compact positive kernel, may be used to obtain limit theorems for Markov chains or to describe stochastic properties of dynamical systems.A general framework for this method is given and then applied to trea

Markov Chains with Stationary Transition
✍ Kai Lai Chung (auth.) 📂 Library 📅 1960 🏛 Springer-Verlag Berlin Heidelberg 🌐 English

<p>The theory of Markov chains, although a special case of Markov processes, is here developed for its own sake and presented on its own merits. In general, the hypothesis of a denumerable state space, which is the defining hypothesis of what we call a "chain" here, generates more clear-cut question

Markov Chains: With Stationary Transitio
✍ Kai Lai Chung (auth.) 📂 Library 📅 1967 🏛 Springer 🌐 English

From the reviews: <p> J. Neveu, 1962 in Zentralblatt für Mathematik, 92.Band Heft 2, p. 343: "Ce livre écrit par l'un des plus éminents spécialistes en la matière, est un exposé très détaillé de la théorie des processus de Markov définis sur un espace dénombrable d'états et homogènes dans le temps (

Markov chains with stationary transition
✍ Kai Lai Chung 📂 Library 📅 1967 🏛 Springer 🌐 English

From the reviews: <p> J. Neveu, 1962 in Zentralblatt fГјr Mathematik, 92.Band Heft 2, p. 343: "Ce livre Г©crit par l'un des plus Г©minents spГ©cialistes en la matiГЁre, est un exposГ© trГЁs dГ©taillГ© de la thГ©orie des processus de Markov dГ©finis sur un espace dГ©nombrable d'Г©tats et homogГЁne