Dependence with Complete Connections and Its Applications (Paperback)

Marius Iosifescu

ISBN 10: 0521101808 / ISBN 13: 9780521101806

Edité par Cambridge University Press, Cambridge, 2009

A propos de cet article

Paperback. Dependence with complete connections is a more general type of stochastic process than the well-known Markovian dependence, accounting for a complete history of a stochastic evolution. This book is an authoritative survey of knowledge of the subject, dealing with the basic theoretical understanding and also with applications. These arise in a variety of situations as diverse as stochastic models of learning, branching processes in random environments, continued fractions and dynamical systems. Thus the book will appeal to mathematicians working in probability theory, ergodic theory and number theory, as well as applied mathematicians, engineers, biologists and social scientists interested in applications of stochastic methods. Dependence with complete connections is a more general type of stochastic process than the well-known Markovian dependence, accounting for a complete history of a stochastic evolution. This book is an authoritative survey of knowledge of the subject, dealing with the basic theoretical understanding and also with applications. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

N° de réf. du vendeur 9780521101806

Détails bibliographiques

• Titre: Dependence with Complete Connections and Its Applications (Paperback)
• Éditeur: Cambridge University Press, Cambridge
• Date de parution: 2009
• Langue: anglais
• ISBN à 10 chiffres: 0521101808
• ISBN à 13 chiffres: 9780521101806
• Reliure: Paperback
• État de l'article: new

A propos de ce titre

Synopsis

The book will appeal to mathematicians working in probability theory, ergodic theory and number theory

Présentation de l'éditeur

Dependence with complete connections is a more general type of stochastic process than the well-known Markovian dependence, accounting for a complete history of a stochastic evolution. This book is an authoritative survey of knowledge of the subject, dealing with the basic theoretical understanding and also with applications. These arise in a variety of situations as diverse as stochastic models of learning, branching processes in random environments, continued fractions and dynamical systems. Thus the book will appeal to mathematicians working in probability theory, ergodic theory and number theory, as well as applied mathematicians, engineers, biologists and social scientists interested in applications of stochastic methods.